diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..6d58dcf
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,2 @@
+.bundle
+bayesdata.yml
diff --git a/.ruby-version b/.ruby-version
new file mode 100644
index 0000000..ac2cdeb
--- /dev/null
+++ b/.ruby-version
@@ -0,0 +1 @@
+2.1.3
diff --git a/CHANGELOG.md b/CHANGELOG.md
new file mode 100644
index 0000000..27e53de
--- /dev/null
+++ b/CHANGELOG.md
@@ -0,0 +1,10 @@
+# Revisions
+##0.5.0
+* Lots of refactoring, cleanup, making methods private, etc.
+* Added tests
+* Removed uid from train/untrain - couldn't think of a good use case, and the logic didn't seem right since the system doesn't keep track of which call to train created a token the untrain option would blindly remove them.
+* Changed BayesData to BayesPool since that seems more explanatory
+* Moved some pool manipulation functions into BayesPool for better encapsulation
+* Add to_json method
+* Removed data_class from Bayes initializer since I couldn't think of a reason to make that configurable
+* Create corpus in build cache instead of maintaining it in parallel
\ No newline at end of file
diff --git a/COPYING b/COPYING
new file mode 100644
index 0000000..20d40b6
--- /dev/null
+++ b/COPYING
@@ -0,0 +1,674 @@
+ GNU GENERAL PUBLIC LICENSE
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+OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
+THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
+IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
+ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
+
+ 16. Limitation of Liability.
+
+ IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
+WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
+THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
+GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
+USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
+DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
+PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
+EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
+SUCH DAMAGES.
+
+ 17. Interpretation of Sections 15 and 16.
+
+ If the disclaimer of warranty and limitation of liability provided
+above cannot be given local legal effect according to their terms,
+reviewing courts shall apply local law that most closely approximates
+an absolute waiver of all civil liability in connection with the
+Program, unless a warranty or assumption of liability accompanies a
+copy of the Program in return for a fee.
+
+ END OF TERMS AND CONDITIONS
+
+ How to Apply These Terms to Your New Programs
+
+ If you develop a new program, and you want it to be of the greatest
+possible use to the public, the best way to achieve this is to make it
+free software which everyone can redistribute and change under these terms.
+
+ To do so, attach the following notices to the program. It is safest
+to attach them to the start of each source file to most effectively
+state the exclusion of warranty; and each file should have at least
+the "copyright" line and a pointer to where the full notice is found.
+
+
+ Copyright (C)
+
+ This program is free software: you can redistribute it and/or modify
+ it under the terms of the GNU General Public License as published by
+ the Free Software Foundation, either version 3 of the License, or
+ (at your option) any later version.
+
+ This program is distributed in the hope that it will be useful,
+ but WITHOUT ANY WARRANTY; without even the implied warranty of
+ MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+ GNU General Public License for more details.
+
+ You should have received a copy of the GNU General Public License
+ along with this program. If not, see .
+
+Also add information on how to contact you by electronic and paper mail.
+
+ If the program does terminal interaction, make it output a short
+notice like this when it starts in an interactive mode:
+
+ Copyright (C)
+ This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
+ This is free software, and you are welcome to redistribute it
+ under certain conditions; type `show c' for details.
+
+The hypothetical commands `show w' and `show c' should show the appropriate
+parts of the General Public License. Of course, your program's commands
+might be different; for a GUI interface, you would use an "about box".
+
+ You should also get your employer (if you work as a programmer) or school,
+if any, to sign a "copyright disclaimer" for the program, if necessary.
+For more information on this, and how to apply and follow the GNU GPL, see
+.
+
+ The GNU General Public License does not permit incorporating your program
+into proprietary programs. If your program is a subroutine library, you
+may consider it more useful to permit linking proprietary applications with
+the library. If this is what you want to do, use the GNU Lesser General
+Public License instead of this License. But first, please read
+.
\ No newline at end of file
diff --git a/COPYING.LESSER b/COPYING.LESSER
new file mode 100644
index 0000000..20d40b6
--- /dev/null
+++ b/COPYING.LESSER
@@ -0,0 +1,674 @@
+ GNU GENERAL PUBLIC LICENSE
+ Version 3, 29 June 2007
+
+ Copyright (C) 2007 Free Software Foundation, Inc.
+ Everyone is permitted to copy and distribute verbatim copies
+ of this license document, but changing it is not allowed.
+
+ Preamble
+
+ The GNU General Public License is a free, copyleft license for
+software and other kinds of works.
+
+ The licenses for most software and other practical works are designed
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+share and change all versions of a program--to make sure it remains free
+software for all its users. We, the Free Software Foundation, use the
+GNU General Public License for most of our software; it applies also to
+any other work released this way by its authors. You can apply it to
+your programs, too.
+
+ When we speak of free software, we are referring to freedom, not
+price. Our General Public Licenses are designed to make sure that you
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+
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+you modify it: responsibilities to respect the freedom of others.
+
+ For example, if you distribute copies of such a program, whether
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+
+ Developers that use the GNU GPL protect your rights with two steps:
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+
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+
+ Some devices are designed to deny users access to install or run
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+
+ TERMS AND CONDITIONS
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+or that patent license was granted, prior to 28 March 2007.
+
+ Nothing in this License shall be construed as excluding or limiting
+any implied license or other defenses to infringement that may
+otherwise be available to you under applicable patent law.
+
+ 12. No Surrender of Others' Freedom.
+
+ If conditions are imposed on you (whether by court order, agreement or
+otherwise) that contradict the conditions of this License, they do not
+excuse you from the conditions of this License. If you cannot convey a
+covered work so as to satisfy simultaneously your obligations under this
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+not convey it at all. For example, if you agree to terms that obligate you
+to collect a royalty for further conveying from those to whom you convey
+the Program, the only way you could satisfy both those terms and this
+License would be to refrain entirely from conveying the Program.
+
+ 13. Use with the GNU Affero General Public License.
+
+ Notwithstanding any other provision of this License, you have
+permission to link or combine any covered work with a work licensed
+under version 3 of the GNU Affero General Public License into a single
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+section 13, concerning interaction through a network will apply to the
+combination as such.
+
+ 14. Revised Versions of this License.
+
+ The Free Software Foundation may publish revised and/or new versions of
+the GNU General Public License from time to time. Such new versions will
+be similar in spirit to the present version, but may differ in detail to
+address new problems or concerns.
+
+ Each version is given a distinguishing version number. If the
+Program specifies that a certain numbered version of the GNU General
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+option of following the terms and conditions either of that numbered
+version or of any later version published by the Free Software
+Foundation. If the Program does not specify a version number of the
+GNU General Public License, you may choose any version ever published
+by the Free Software Foundation.
+
+ If the Program specifies that a proxy can decide which future
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+public statement of acceptance of a version permanently authorizes you
+to choose that version for the Program.
+
+ Later license versions may give you additional or different
+permissions. However, no additional obligations are imposed on any
+author or copyright holder as a result of your choosing to follow a
+later version.
+
+ 15. Disclaimer of Warranty.
+
+ THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
+APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
+HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
+OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
+THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
+IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
+ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
+
+ 16. Limitation of Liability.
+
+ IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
+WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
+THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
+GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
+USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
+DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
+PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
+EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
+SUCH DAMAGES.
+
+ 17. Interpretation of Sections 15 and 16.
+
+ If the disclaimer of warranty and limitation of liability provided
+above cannot be given local legal effect according to their terms,
+reviewing courts shall apply local law that most closely approximates
+an absolute waiver of all civil liability in connection with the
+Program, unless a warranty or assumption of liability accompanies a
+copy of the Program in return for a fee.
+
+ END OF TERMS AND CONDITIONS
+
+ How to Apply These Terms to Your New Programs
+
+ If you develop a new program, and you want it to be of the greatest
+possible use to the public, the best way to achieve this is to make it
+free software which everyone can redistribute and change under these terms.
+
+ To do so, attach the following notices to the program. It is safest
+to attach them to the start of each source file to most effectively
+state the exclusion of warranty; and each file should have at least
+the "copyright" line and a pointer to where the full notice is found.
+
+
+ Copyright (C)
+
+ This program is free software: you can redistribute it and/or modify
+ it under the terms of the GNU General Public License as published by
+ the Free Software Foundation, either version 3 of the License, or
+ (at your option) any later version.
+
+ This program is distributed in the hope that it will be useful,
+ but WITHOUT ANY WARRANTY; without even the implied warranty of
+ MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+ GNU General Public License for more details.
+
+ You should have received a copy of the GNU General Public License
+ along with this program. If not, see .
+
+Also add information on how to contact you by electronic and paper mail.
+
+ If the program does terminal interaction, make it output a short
+notice like this when it starts in an interactive mode:
+
+ Copyright (C)
+ This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
+ This is free software, and you are welcome to redistribute it
+ under certain conditions; type `show c' for details.
+
+The hypothetical commands `show w' and `show c' should show the appropriate
+parts of the General Public License. Of course, your program's commands
+might be different; for a GUI interface, you would use an "about box".
+
+ You should also get your employer (if you work as a programmer) or school,
+if any, to sign a "copyright disclaimer" for the program, if necessary.
+For more information on this, and how to apply and follow the GNU GPL, see
+.
+
+ The GNU General Public License does not permit incorporating your program
+into proprietary programs. If your program is a subroutine library, you
+may consider it more useful to permit linking proprietary applications with
+the library. If this is what you want to do, use the GNU Lesser General
+Public License instead of this License. But first, please read
+.
\ No newline at end of file
diff --git a/Gemfile b/Gemfile
new file mode 100644
index 0000000..3c05cb9
--- /dev/null
+++ b/Gemfile
@@ -0,0 +1,7 @@
+source 'http://rubygems.org'
+ruby '2.1.3'
+gem 'stemmer'
+
+group :test do
+ gem 'minitest'
+end
diff --git a/Gemfile.lock b/Gemfile.lock
new file mode 100644
index 0000000..21b10ec
--- /dev/null
+++ b/Gemfile.lock
@@ -0,0 +1,12 @@
+GEM
+ remote: http://rubygems.org/
+ specs:
+ minitest (5.4.2)
+ stemmer (1.0.1)
+
+PLATFORMS
+ ruby
+
+DEPENDENCIES
+ minitest
+ stemmer
diff --git a/README.md b/README.md
new file mode 100644
index 0000000..3688827
--- /dev/null
+++ b/README.md
@@ -0,0 +1,40 @@
+# Introduction
+This is a Naive Bayes classifier that can be used to categorize text based on trained "pools".
+Training counts how often each word is used, except for any specified stop words.
+The Bayes::Bishop.guess method tokenizes the message and then calculates for each pool the probability that the message is the same "classification" as that pool.
+For example, you could train the system with one pool of "spam" email and one pool of "non-spam" email. Then you could ask the guess method which pool each incoming message belongs to.
+
+# Usage
+1. Create a Bishop::Bayes object:
+
+ b = Bishop::Bayes.new
+
+2. Train with multiple pools of text:
+
+ b.train('pool1')
+ b.train('pool2')
+ b.train('pool3')
+
+3. Call the guess method with a message to categorize:
+
+ guesses = b.guess('This is a sentence')
+
+ The return value is a hash where the keys are pool names and the values are the probability
+ that the message belongs to that pool.
+
+# Features
+* Stop words may be specified
+
+ b.add_stop_words(an_array_words)
+ b.add_stop_word('word')
+
+* You can include the default stop words list
+
+ b.load_default_stop_words
+
+* You can choose between the default tokenizer, a stemming tokenizer, or a custom tokenizer
+
+ b = Bishop::Bayes.new
+ b = Bishop::Bayes.new(Bishop::StemmingTokenizer)
+ b = Bishop::Bayes.new(CustomTokenizer)
+
diff --git a/Rakefile b/Rakefile
new file mode 100644
index 0000000..2eb8847
--- /dev/null
+++ b/Rakefile
@@ -0,0 +1,30 @@
+require 'rake/testtask'
+require 'rdoc/task'
+
+#desc "Default task: test"
+task :default => [:test]
+
+desc "Run Tests"
+Rake::TestTask.new( :test ) do |t|
+ t.pattern = "test/test_*.rb"
+ t.verbose = true
+end
+
+RDoc::Task.new(:rdoc) do |rdoc|
+ rdoc.main = 'README.md'
+ rdoc.rdoc_files.include 'README.md', 'CHANGELOG.md', "lib/**/*\.rb"
+ rdoc.rdoc_dir = 'docs/rdoc'
+ rdoc.title = "Bayes::Bishop Documentation"
+ rdoc.options << '--line-numbers'
+ rdoc.options << '--fileboxes'
+end
+
+RDoc::Task.new(:rdoc => "rdoc_markdown",:clobber_rdoc => "clobber_rdoc_markdown", :rerdoc => "rerdoc_markdown") do |rdoc|
+ rdoc.main = 'README.md'
+ rdoc.rdoc_files.include 'README.md', 'CHANGELOG.md', "lib/**/*\.rb"
+ rdoc.rdoc_dir = 'docs/md'
+ rdoc.title = "Bayes::Bishop Documentation"
+ rdoc.markup = 'MARKUP'
+ rdoc.options << '--line-numbers'
+ rdoc.options << '--fileboxes'
+end
\ No newline at end of file
diff --git a/bishop.gemspec b/bishop.gemspec
index 1e4f7e6..b1ba8f2 100755
--- a/bishop.gemspec
+++ b/bishop.gemspec
@@ -2,21 +2,21 @@ require 'rubygems'
SPEC = Gem::Specification.new do |s|
s.name = "bishop"
- s.version = "0.4.0"
- s.author = "Matt Mower"
- s.email = "self@mattmower.com"
- s.homepage = "http://rubyforge.org/projects/bishop/"
+ s.version = "0.5.0"
+ s.author = "Richard Harrington"
+ s.email = "richard@maymount.com"
+ s.license = 'LGPL-3.0+'
+ s.homepage = "https://github.com/maymount/bishop"
s.platform = Gem::Platform::RUBY
- s.summary = "Bayesian classification and ART-2 clustering library."
-
- candidates = Dir.glob( "{bin,docs,lib,test}/**/*" )
+ s.summary = "Bayesian classification library. Refactoring of mmowers/bishop version."
+ s.description = "Bayesian classification library. Refactoring of mmowers/bishop version."
+ s.add_runtime_dependency 'stemmer'
+ candidates = Dir.glob( "{docs,lib,test}/**/*" )
s.files = candidates.delete_if do |item|
item.include?( "CVS" ) || item.include?( "rdoc" )
end
+ s.extra_rdoc_files = ['README.md','CHANGELOG.md','COPYING','COPYING.LESSER']
s.require_path = "lib"
-# s.autorequire = "bishop"
s.has_rdoc = true
-
- #s.add_dependency( "stemmer", ">= 1.0.1" )
end
\ No newline at end of file
diff --git a/docs/md/Bishop.html b/docs/md/Bishop.html
new file mode 100644
index 0000000..030df55
--- /dev/null
+++ b/docs/md/Bishop.html
@@ -0,0 +1,202 @@
+
+
+
+
+
+
+module Bishop - Bayes::Bishop Documentation
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
tokenizer is the name of the class that will separate the input into
+tokens. See SimpleTokenizer and StemmingTokenizer for more information.
+Combiner defaults to a block that calls Bishop.robinson
+
+
+
+
+
+
# File lib/bayes/bishop.rb, line 139
+definitialize( tokenizer = SimpleTokenizer, &combiner )
+ @tokenizer = tokenizer.new
+ @combiner = combiner||Proc.new { |probs,ignore|Bishop.robinson( probs, ignore ) }
+ @pools = {} # hash, key = pool name, value = BayesPool class
+ @cache = {} # created by calling build_cache, contains raw probabilities
+ @corpus_data = nil# created when corpus method is called, contains token totals
+ @dirty = true# indicates that cache and corpus_data are invalid
+ @stop_words = []
+end
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
Public Instance Methods
+
+
+
+
+
+
+ add_stop_word( word )
+
+ click to toggle source
+
+
+
+
+
+
+
Add the specified stop word
+
+
+
+
+
+
# File lib/bayes/bishop.rb, line 199
+defadd_stop_word( word )
+ @stop_words<<word.downcaseif!@stop_words.include?(word.downcase)
+end
+
+
+
+
+
+
+
+
+
+
+
+
+
+ add_stop_words( words )
+
+ click to toggle source
+
+
+
+
+
+
+
Add an array of stop words
+
+
+
+
+
+
# File lib/bayes/bishop.rb, line 194
+defadd_stop_words( words )
+ words.each { |word|add_stop_wordwordif!word.empty? }
+end
+
+
+
+
+
+
+
+
+
+
+
+
+
+ guess( msg )
+
+ click to toggle source
+
+
+
+
+
+
+
Call this method to classify a “message”. The return value will be a hash,
+with the pool name is the key and the probability is the value, for each
+pool which is a likely match for the message.
+
+
+
+
+
+
# File lib/bayes/bishop.rb, line 302
+defguess( msg )
+ tokens = get_tokens( msg )
+ res = {}
+
+ build_cacheifdirty?
+
+ @cache.eachdo|pool_name,pool|
+ p = get_probs( pool, tokens )
+ ifp.length!=0
+ res[pool_name] = @combiner.call( p, pool_name )
+ end
+ end
+
+ h = Hash.new
+ res.sort.each { |a|h[a[0]] = a[1] }
+ h
+end
+
+
+
+
+
+
+
+
+
+
+
+
+
+ load_default_stop_words()
+
+ click to toggle source
+
+
+
+
+
+
+
Load the default stop word list included with Bishop
Remove the input from the given pool If the input is a string it is passed
+through the configured Tokenizer. Otherwise, if it is an array it is just
+added.
Lots of refactoring, cleanup, making methods private, etc.
+
+
Added tests
+
+
Removed uid from train/untrain - couldn't think of a good use case, and
+the logic didn't seem right since the system doesn't keep track of
+which call to train created a token the untrain option would blindly remove
+them.
+
+
Changed BayesData to BayesPool since that seems more explanatory
+
+
Moved some pool manipulation functions into BayesPool for better
+encapsulation
+
+
Add to_json method
+
+
Removed data_class from Bayes initializer since I couldn't think of a
+reason to make that configurable
+
+
Create corpus in build cache instead of maintaining it in parallel
This is a Naive Bayes classifier that can be used to categorize text based
+on trained “pools”. Training counts how often each word is used, except for
+any specified stop words. The Bayes::Bishop.guess method tokenizes the
+message and then calculates for each pool the probability that the message
+is the same “classification” as that pool. For example, you could train the
+system with one pool of “spam” email and one pool of “non-spam” email. Then
+you could ask the guess method which pool each incoming message belongs to.
You can choose between the default tokenizer, a stemming tokenizer, or a
+custom tokenizer
+
+
b = Bishop::Bayes.new
+b = Bishop::Bayes.new(Bishop::StemmingTokenizer)
+b = Bishop::Bayes.new(CustomTokenizer)
+
+
+
+
+
+
+
diff --git a/docs/md/created.rid b/docs/md/created.rid
new file mode 100644
index 0000000..427b56f
--- /dev/null
+++ b/docs/md/created.rid
@@ -0,0 +1,4 @@
+Sun, 02 Nov 2014 22:30:34 -0800
+README.md Sun, 02 Nov 2014 22:18:55 -0800
+CHANGELOG.md Sun, 02 Nov 2014 21:13:42 -0800
+lib/bayes/bishop.rb Sun, 02 Nov 2014 22:30:31 -0800
diff --git a/docs/md/fonts.css b/docs/md/fonts.css
new file mode 100644
index 0000000..e9e7211
--- /dev/null
+++ b/docs/md/fonts.css
@@ -0,0 +1,167 @@
+/*
+ * Copyright 2010, 2012 Adobe Systems Incorporated (http://www.adobe.com/),
+ * with Reserved Font Name "Source". All Rights Reserved. Source is a
+ * trademark of Adobe Systems Incorporated in the United States and/or other
+ * countries.
+ *
+ * This Font Software is licensed under the SIL Open Font License, Version
+ * 1.1.
+ *
+ * This license is copied below, and is also available with a FAQ at:
+ * http://scripts.sil.org/OFL
+ */
+
+@font-face {
+ font-family: "Source Code Pro";
+ font-style: normal;
+ font-weight: 400;
+ src: local("Source Code Pro"),
+ local("SourceCodePro-Regular"),
+ url("fonts/SourceCodePro-Regular.ttf") format("truetype");
+}
+
+@font-face {
+ font-family: "Source Code Pro";
+ font-style: normal;
+ font-weight: 700;
+ src: local("Source Code Pro Bold"),
+ local("SourceCodePro-Bold"),
+ url("fonts/SourceCodePro-Bold.ttf") format("truetype");
+}
+
+/*
+ * Copyright (c) 2010, Łukasz Dziedzic (dziedzic@typoland.com),
+ * with Reserved Font Name Lato.
+ *
+ * This Font Software is licensed under the SIL Open Font License, Version
+ * 1.1.
+ *
+ * This license is copied below, and is also available with a FAQ at:
+ * http://scripts.sil.org/OFL
+ */
+
+@font-face {
+ font-family: "Lato";
+ font-style: normal;
+ font-weight: 300;
+ src: local("Lato Light"),
+ local("Lato-Light"),
+ url("fonts/Lato-Light.ttf") format("truetype");
+}
+
+@font-face {
+ font-family: "Lato";
+ font-style: italic;
+ font-weight: 300;
+ src: local("Lato Light Italic"),
+ local("Lato-LightItalic"),
+ url("fonts/Lato-LightItalic.ttf") format("truetype");
+}
+
+@font-face {
+ font-family: "Lato";
+ font-style: normal;
+ font-weight: 700;
+ src: local("Lato Regular"),
+ local("Lato-Regular"),
+ url("fonts/Lato-Regular.ttf") format("truetype");
+}
+
+@font-face {
+ font-family: "Lato";
+ font-style: italic;
+ font-weight: 700;
+ src: local("Lato Italic"),
+ local("Lato-Italic"),
+ url("fonts/Lato-RegularItalic.ttf") format("truetype");
+}
+
+/*
+ * -----------------------------------------------------------
+ * SIL OPEN FONT LICENSE Version 1.1 - 26 February 2007
+ * -----------------------------------------------------------
+ *
+ * PREAMBLE
+ * The goals of the Open Font License (OFL) are to stimulate worldwide
+ * development of collaborative font projects, to support the font creation
+ * efforts of academic and linguistic communities, and to provide a free and
+ * open framework in which fonts may be shared and improved in partnership
+ * with others.
+ *
+ * The OFL allows the licensed fonts to be used, studied, modified and
+ * redistributed freely as long as they are not sold by themselves. The
+ * fonts, including any derivative works, can be bundled, embedded,
+ * redistributed and/or sold with any software provided that any reserved
+ * names are not used by derivative works. The fonts and derivatives,
+ * however, cannot be released under any other type of license. The
+ * requirement for fonts to remain under this license does not apply
+ * to any document created using the fonts or their derivatives.
+ *
+ * DEFINITIONS
+ * "Font Software" refers to the set of files released by the Copyright
+ * Holder(s) under this license and clearly marked as such. This may
+ * include source files, build scripts and documentation.
+ *
+ * "Reserved Font Name" refers to any names specified as such after the
+ * copyright statement(s).
+ *
+ * "Original Version" refers to the collection of Font Software components as
+ * distributed by the Copyright Holder(s).
+ *
+ * "Modified Version" refers to any derivative made by adding to, deleting,
+ * or substituting -- in part or in whole -- any of the components of the
+ * Original Version, by changing formats or by porting the Font Software to a
+ * new environment.
+ *
+ * "Author" refers to any designer, engineer, programmer, technical
+ * writer or other person who contributed to the Font Software.
+ *
+ * PERMISSION & CONDITIONS
+ * Permission is hereby granted, free of charge, to any person obtaining
+ * a copy of the Font Software, to use, study, copy, merge, embed, modify,
+ * redistribute, and sell modified and unmodified copies of the Font
+ * Software, subject to the following conditions:
+ *
+ * 1) Neither the Font Software nor any of its individual components,
+ * in Original or Modified Versions, may be sold by itself.
+ *
+ * 2) Original or Modified Versions of the Font Software may be bundled,
+ * redistributed and/or sold with any software, provided that each copy
+ * contains the above copyright notice and this license. These can be
+ * included either as stand-alone text files, human-readable headers or
+ * in the appropriate machine-readable metadata fields within text or
+ * binary files as long as those fields can be easily viewed by the user.
+ *
+ * 3) No Modified Version of the Font Software may use the Reserved Font
+ * Name(s) unless explicit written permission is granted by the corresponding
+ * Copyright Holder. This restriction only applies to the primary font name as
+ * presented to the users.
+ *
+ * 4) The name(s) of the Copyright Holder(s) or the Author(s) of the Font
+ * Software shall not be used to promote, endorse or advertise any
+ * Modified Version, except to acknowledge the contribution(s) of the
+ * Copyright Holder(s) and the Author(s) or with their explicit written
+ * permission.
+ *
+ * 5) The Font Software, modified or unmodified, in part or in whole,
+ * must be distributed entirely under this license, and must not be
+ * distributed under any other license. The requirement for fonts to
+ * remain under this license does not apply to any document created
+ * using the Font Software.
+ *
+ * TERMINATION
+ * This license becomes null and void if any of the above conditions are
+ * not met.
+ *
+ * DISCLAIMER
+ * THE FONT SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+ * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTIES OF
+ * MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT
+ * OF COPYRIGHT, PATENT, TRADEMARK, OR OTHER RIGHT. IN NO EVENT SHALL THE
+ * COPYRIGHT HOLDER BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+ * INCLUDING ANY GENERAL, SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL
+ * DAMAGES, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF THE USE OR INABILITY TO USE THE FONT SOFTWARE OR FROM
+ * OTHER DEALINGS IN THE FONT SOFTWARE.
+ */
+
diff --git a/docs/md/fonts/Lato-Light.ttf b/docs/md/fonts/Lato-Light.ttf
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+
+
+
+
+
+
+Bayes::Bishop Documentation
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
This is a Naive Bayes classifier that can be used to categorize text based
+on trained “pools”. Training counts how often each word is used, except for
+any specified stop words. The Bayes::Bishop.guess method tokenizes the
+message and then calculates for each pool the probability that the message
+is the same “classification” as that pool. For example, you could train the
+system with one pool of “spam” email and one pool of “non-spam” email. Then
+you could ask the guess method which pool each incoming message belongs to.
tokenizer is the name of the class that will separate the input into
+tokens. See SimpleTokenizer and StemmingTokenizer for more information.
+Combiner defaults to a block that calls Bishop.robinson
+
+
+
+
+
+
# File lib/bayes/bishop.rb, line 139
+definitialize( tokenizer = SimpleTokenizer, &combiner )
+ @tokenizer = tokenizer.new
+ @combiner = combiner||Proc.new { |probs,ignore|Bishop.robinson( probs, ignore ) }
+ @pools = {} # hash, key = pool name, value = BayesPool class
+ @cache = {} # created by calling build_cache, contains raw probabilities
+ @corpus_data = nil# created when corpus method is called, contains token totals
+ @dirty = true# indicates that cache and corpus_data are invalid
+ @stop_words = []
+end
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
Public Instance Methods
+
+
+
+
+
+
+ add_stop_word( word )
+
+ click to toggle source
+
+
+
+
+
+
+
Add the specified stop word
+
+
+
+
+
+
# File lib/bayes/bishop.rb, line 199
+defadd_stop_word( word )
+ @stop_words<<word.downcaseif!@stop_words.include?(word.downcase)
+end
+
+
+
+
+
+
+
+
+
+
+
+
+
+ add_stop_words( words )
+
+ click to toggle source
+
+
+
+
+
+
+
Add an array of stop words
+
+
+
+
+
+
# File lib/bayes/bishop.rb, line 194
+defadd_stop_words( words )
+ words.each { |word|add_stop_wordwordif!word.empty? }
+end
+
+
+
+
+
+
+
+
+
+
+
+
+
+ guess( msg )
+
+ click to toggle source
+
+
+
+
+
+
+
Call this method to classify a “message”. The return value will be a hash,
+with the pool name is the key and the probability is the value, for each
+pool which is a likely match for the message.
+
+
+
+
+
+
# File lib/bayes/bishop.rb, line 302
+defguess( msg )
+ tokens = get_tokens( msg )
+ res = {}
+
+ build_cacheifdirty?
+
+ @cache.eachdo|pool_name,pool|
+ p = get_probs( pool, tokens )
+ ifp.length!=0
+ res[pool_name] = @combiner.call( p, pool_name )
+ end
+ end
+
+ h = Hash.new
+ res.sort.each { |a|h[a[0]] = a[1] }
+ h
+end
+
+
+
+
+
+
+
+
+
+
+
+
+
+ load_default_stop_words()
+
+ click to toggle source
+
+
+
+
+
+
+
Load the default stop word list included with Bishop
Remove the input from the given pool If the input is a string it is passed
+through the configured Tokenizer. Otherwise, if it is an array it is just
+added.
Lots of refactoring, cleanup, making methods private, etc.
+
+
Added tests
+
+
Removed uid from train/untrain - couldn't think of a good use case, and
+the logic didn't seem right since the system doesn't keep track of
+which call to train created a token the untrain option would blindly remove
+them.
+
+
Changed BayesData to BayesPool since that seems more explanatory
+
+
Moved some pool manipulation functions into BayesPool for better
+encapsulation
+
+
Add to_json method
+
+
Removed data_class from Bayes initializer since I couldn't think of a
+reason to make that configurable
+
+
Create corpus in build cache instead of maintaining it in parallel
This is a Naive Bayes classifier that can be used to categorize text based
+on trained “pools”. Training counts how often each word is used, except for
+any specified stop words. The Bayes::Bishop.guess method tokenizes the
+message and then calculates for each pool the probability that the message
+is the same “classification” as that pool. For example, you could train the
+system with one pool of “spam” email and one pool of “non-spam” email. Then
+you could ask the guess method which pool each incoming message belongs to.
You can choose between the default tokenizer, a stemming tokenizer, or a
+custom tokenizer
+
+
b = Bishop::Bayes.new
+b = Bishop::Bayes.new(Bishop::StemmingTokenizer)
+b = Bishop::Bayes.new(CustomTokenizer)
+
+
+
+
+
+
+
diff --git a/docs/rdoc/created.rid b/docs/rdoc/created.rid
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--- /dev/null
+++ b/docs/rdoc/created.rid
@@ -0,0 +1,4 @@
+Sun, 02 Nov 2014 22:30:34 -0800
+README.md Sun, 02 Nov 2014 22:18:55 -0800
+CHANGELOG.md Sun, 02 Nov 2014 21:13:42 -0800
+lib/bayes/bishop.rb Sun, 02 Nov 2014 22:30:31 -0800
diff --git a/docs/rdoc/fonts.css b/docs/rdoc/fonts.css
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+++ b/docs/rdoc/fonts.css
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+/*
+ * Copyright 2010, 2012 Adobe Systems Incorporated (http://www.adobe.com/),
+ * with Reserved Font Name "Source". All Rights Reserved. Source is a
+ * trademark of Adobe Systems Incorporated in the United States and/or other
+ * countries.
+ *
+ * This Font Software is licensed under the SIL Open Font License, Version
+ * 1.1.
+ *
+ * This license is copied below, and is also available with a FAQ at:
+ * http://scripts.sil.org/OFL
+ */
+
+@font-face {
+ font-family: "Source Code Pro";
+ font-style: normal;
+ font-weight: 400;
+ src: local("Source Code Pro"),
+ local("SourceCodePro-Regular"),
+ url("fonts/SourceCodePro-Regular.ttf") format("truetype");
+}
+
+@font-face {
+ font-family: "Source Code Pro";
+ font-style: normal;
+ font-weight: 700;
+ src: local("Source Code Pro Bold"),
+ local("SourceCodePro-Bold"),
+ url("fonts/SourceCodePro-Bold.ttf") format("truetype");
+}
+
+/*
+ * Copyright (c) 2010, Łukasz Dziedzic (dziedzic@typoland.com),
+ * with Reserved Font Name Lato.
+ *
+ * This Font Software is licensed under the SIL Open Font License, Version
+ * 1.1.
+ *
+ * This license is copied below, and is also available with a FAQ at:
+ * http://scripts.sil.org/OFL
+ */
+
+@font-face {
+ font-family: "Lato";
+ font-style: normal;
+ font-weight: 300;
+ src: local("Lato Light"),
+ local("Lato-Light"),
+ url("fonts/Lato-Light.ttf") format("truetype");
+}
+
+@font-face {
+ font-family: "Lato";
+ font-style: italic;
+ font-weight: 300;
+ src: local("Lato Light Italic"),
+ local("Lato-LightItalic"),
+ url("fonts/Lato-LightItalic.ttf") format("truetype");
+}
+
+@font-face {
+ font-family: "Lato";
+ font-style: normal;
+ font-weight: 700;
+ src: local("Lato Regular"),
+ local("Lato-Regular"),
+ url("fonts/Lato-Regular.ttf") format("truetype");
+}
+
+@font-face {
+ font-family: "Lato";
+ font-style: italic;
+ font-weight: 700;
+ src: local("Lato Italic"),
+ local("Lato-Italic"),
+ url("fonts/Lato-RegularItalic.ttf") format("truetype");
+}
+
+/*
+ * -----------------------------------------------------------
+ * SIL OPEN FONT LICENSE Version 1.1 - 26 February 2007
+ * -----------------------------------------------------------
+ *
+ * PREAMBLE
+ * The goals of the Open Font License (OFL) are to stimulate worldwide
+ * development of collaborative font projects, to support the font creation
+ * efforts of academic and linguistic communities, and to provide a free and
+ * open framework in which fonts may be shared and improved in partnership
+ * with others.
+ *
+ * The OFL allows the licensed fonts to be used, studied, modified and
+ * redistributed freely as long as they are not sold by themselves. The
+ * fonts, including any derivative works, can be bundled, embedded,
+ * redistributed and/or sold with any software provided that any reserved
+ * names are not used by derivative works. The fonts and derivatives,
+ * however, cannot be released under any other type of license. The
+ * requirement for fonts to remain under this license does not apply
+ * to any document created using the fonts or their derivatives.
+ *
+ * DEFINITIONS
+ * "Font Software" refers to the set of files released by the Copyright
+ * Holder(s) under this license and clearly marked as such. This may
+ * include source files, build scripts and documentation.
+ *
+ * "Reserved Font Name" refers to any names specified as such after the
+ * copyright statement(s).
+ *
+ * "Original Version" refers to the collection of Font Software components as
+ * distributed by the Copyright Holder(s).
+ *
+ * "Modified Version" refers to any derivative made by adding to, deleting,
+ * or substituting -- in part or in whole -- any of the components of the
+ * Original Version, by changing formats or by porting the Font Software to a
+ * new environment.
+ *
+ * "Author" refers to any designer, engineer, programmer, technical
+ * writer or other person who contributed to the Font Software.
+ *
+ * PERMISSION & CONDITIONS
+ * Permission is hereby granted, free of charge, to any person obtaining
+ * a copy of the Font Software, to use, study, copy, merge, embed, modify,
+ * redistribute, and sell modified and unmodified copies of the Font
+ * Software, subject to the following conditions:
+ *
+ * 1) Neither the Font Software nor any of its individual components,
+ * in Original or Modified Versions, may be sold by itself.
+ *
+ * 2) Original or Modified Versions of the Font Software may be bundled,
+ * redistributed and/or sold with any software, provided that each copy
+ * contains the above copyright notice and this license. These can be
+ * included either as stand-alone text files, human-readable headers or
+ * in the appropriate machine-readable metadata fields within text or
+ * binary files as long as those fields can be easily viewed by the user.
+ *
+ * 3) No Modified Version of the Font Software may use the Reserved Font
+ * Name(s) unless explicit written permission is granted by the corresponding
+ * Copyright Holder. This restriction only applies to the primary font name as
+ * presented to the users.
+ *
+ * 4) The name(s) of the Copyright Holder(s) or the Author(s) of the Font
+ * Software shall not be used to promote, endorse or advertise any
+ * Modified Version, except to acknowledge the contribution(s) of the
+ * Copyright Holder(s) and the Author(s) or with their explicit written
+ * permission.
+ *
+ * 5) The Font Software, modified or unmodified, in part or in whole,
+ * must be distributed entirely under this license, and must not be
+ * distributed under any other license. The requirement for fonts to
+ * remain under this license does not apply to any document created
+ * using the Font Software.
+ *
+ * TERMINATION
+ * This license becomes null and void if any of the above conditions are
+ * not met.
+ *
+ * DISCLAIMER
+ * THE FONT SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+ * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTIES OF
+ * MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT
+ * OF COPYRIGHT, PATENT, TRADEMARK, OR OTHER RIGHT. IN NO EVENT SHALL THE
+ * COPYRIGHT HOLDER BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+ * INCLUDING ANY GENERAL, SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL
+ * DAMAGES, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF THE USE OR INABILITY TO USE THE FONT SOFTWARE OR FROM
+ * OTHER DEALINGS IN THE FONT SOFTWARE.
+ */
+
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+
+
+
+
+
+
+Bayes::Bishop Documentation
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
This is a Naive Bayes classifier that can be used to categorize text based
+on trained “pools”. Training counts how often each word is used, except for
+any specified stop words. The Bayes::Bishop.guess method tokenizes the
+message and then calculates for each pool the probability that the message
+is the same “classification” as that pool. For example, you could train the
+system with one pool of “spam” email and one pool of “non-spam” email. Then
+you could ask the guess method which pool each incoming message belongs to.
+
+
+
+
+
diff --git a/lib/bayes/bishop.rb b/lib/bayes/bishop.rb
index 320b5ad..b6a7381 100755
--- a/lib/bayes/bishop.rb
+++ b/lib/bayes/bishop.rb
@@ -1,95 +1,203 @@
+# This is a Naive Bayes classifier that can be used to categorize text based on trained "pools".
+#
+# Copyright 2014, Maymount Enterprises, Ltd.
#
-# This module is a port to the Ruby language of the Reverend Bayesian classifier distributed
-# as part of the Divmod project (which is Copyright 2003 Amir Bakhtiar
+# It is a port to the Ruby language of the Divmod project (which is Copyright 2003 Amir Bakhtiar
+# and based on the Ruby port, Copyright 2005 by Matt Mower
#
-# This Ruby port is Copyright 2005 Matt Mower and is free software;
-# you can distribute it and/or modify it under the terms of version 2.1 of the GNU
-# Lesser General Public License as published by the Free Software Foundation.
+# This program is free software: you can redistribute it and/or modify
+# it under the terms of the GNU Lesser Public License as published by
+# the Free Software Foundation, either version 3 of the License, or
+# (at your option) any later version.
#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+# GNU Lesser Public License for more details.
+#
+# You should have received a copy of the GNU Lesser Public License
+# along with this program. If not, see .
+#
+
require 'yaml'
require 'stemmer'
+require 'json'
module Bishop
- #
- # As at v1.8 Ruby's YAML persists Hashes using special processing rather
- # than by dumping it's instance variables, hence no instance variables
- # in a Hash subclass get dumped either.
- #
- class BayesData
-
- attr_accessor :token_count, :train_count, :name
- attr_reader :training, :data
+ class BayesPool #:nodoc:
+ include Enumerable
+
+ # Sum of token counts in the pool
+ attr_reader :token_count
+
+ # Number of times train has been called for this pool
+ attr_accessor :train_count
+
+ # Hash that contains counts for all tokens
+ attr_reader :data
- def initialize( name = '', pool = nil )
- @name = name
- @training = []
- @pool = pool
+ def initialize
@data = Hash.new( 0.0 )
- self.token_count = 0
- self.train_count = 0
+ @token_count = 0
+ @train_count = 0
end
- def trained_on?( item )
- self.training.include? item
+ # Iterate through the tokens in the pool
+ def each
+ @data.each
end
def to_s
- ""
+ ""
+ end
+
+ # Convert the pool into an array of the format [['token1',count1],['token2',count2],...]
+ def to_a
+ @data.to_a
end
+ # Return all of the tokens in the pool
+ def tokens
+ @data.keys.sort
+ end
+
+ # Return the number of tokens in the pool
+ def num_tokens
+ @data.length
+ end
+
+ # Add a token to the pool, incrementing its count value, and updating the token_value
+ def add_token token, count = 1
+ if @data.has_key?(token)
+ @data[token] = @data[token] + count
+ else
+ @data[token] = count
+ end
+
+ @token_count = @token_count + count
+ end
+
+ # Set the count for a the specified token
+ def []= token, count
+ add_token(token,count)
+ end
+
+ # Get the count for the specified token
+ def [] token
+ @data[token]
+ end
+
+ # Merge another pool into the current pool
+ def merge(other_pool)
+ other_pool.data.each { |token,count| add_token(token,count) }
+ end
+
+ # Decrement the token count and remove the token if the count is 0
+ def remove_token token, count = 1
+ @data[token] -= count
+ @data.delete(token) if @data[token] < 1
+ @token_count = @token_count - count
+ end
end
# A tokenizer class which splits words removing non word characters except hyphens.
class SimpleTokenizer
- def tokenize( item, stop_words )
+ def tokenize( item, stop_words=[] )
item.split( /\s+/ ).map do |i|
- token = i.split( /\-/ ).map { |token| token.downcase.gsub( /\W/, "" ) }.join( "-" )
+ i.split( /\-/ ).map { |token| token.downcase.gsub( /\W/, "" ) }.join( "-" )
end.reject { |t| t == "" || t == "-" || stop_words.detect { |w| w == t } }
end
end
# A tokenizer which, having split words, reduces them to porter stemmed tokens
class StemmingTokenizer < SimpleTokenizer
- def tokenize( item, stop_words )
+ def tokenize( item, stop_words=[] )
super( item, stop_words ).map { |word| word.stem }
end
end
class Bayes
- attr_accessor :dirty, :train_count, :pools, :tokenizer, :data_class, :corpus, :cache, :combiner
- attr_reader :data_class, :stop_words
+ # instance of Tokenizer that handles tokenization
+ attr_accessor :tokenizer
+
+ # Block called to combine probabilities. Set to Bishop.robinson by default
+ attr_accessor :combiner
+
+ # An array containing stop words that the tokenizer will ignore
+ attr_reader :stop_words
+
+ @dirty = true # set to true for any changes, false when pool_probs is called
+ @corpus_data = nil # __Corpus__ pool, created when corpus method called
+ @cache = nil # hash of BayesPool objects that contain probabilities instead of counts
- def initialize( tokenizer = SimpleTokenizer, data_class = BayesData, &combiner )
+ # tokenizer is the name of the class that will separate the input into tokens.
+ # See SimpleTokenizer and StemmingTokenizer for more information.
+ # Combiner defaults to a block that calls Bishop.robinson
+ def initialize( tokenizer = SimpleTokenizer, &combiner )
@tokenizer = tokenizer.new
@combiner = combiner || Proc.new { |probs,ignore| Bishop.robinson( probs, ignore ) }
- @data_class = data_class
- @pools = {}
- @corpus = new_pool( '__Corpus__' )
- @pools['__Corpus__'] = @corpus
- @train_count = 0
- @dirty = true
+ @pools = {} # hash, key = pool name, value = BayesPool class
+ @cache = {} # created by calling build_cache, contains raw probabilities
+ @corpus_data = nil # created when corpus method is called, contains token totals
+ @dirty = true # indicates that cache and corpus_data are invalid
@stop_words = []
end
+
+
+ #
+ # == POOLS
+ #
+
+ # Get the pool specified by name
+ def pool pool_name
+ @pools[pool_name]
+ end
- def commit
- self.save
+ # Get a list of pools
+ def pool_names
+ @pools.keys.sort
+ end
+
+ # Create a new, empty, pool without training.
+ def new_pool( pool_name )
+ @dirty = true
+ @pools[ pool_name ] ||= BayesPool.new
end
- def dirty?
- self.dirty
+ # Remove the given pool
+ def remove_pool( pool_name )
+ @dirty = true
+ @pools.delete( pool_name )
+ end
+
+ # Rename the given pool
+ def rename_pool( pool_name, new_name )
+ @pools[new_name] = @pools[pool_name]
+ @pools.delete( pool_name )
+ @dirty = true
+ end
+
+ # Merge the contents of the source pool into the destination destination pool.
+ def merge_pools( dest_name, source_name )
+ @pools[dest_name].merge(@pools[source_name])
+ @dirty = true
end
- # Add each of the specified stop words
+ #
+ # == STOP WORDS
+ #
+
+ # Add an array of stop words
def add_stop_words( words )
- words.each { |word| add_stop_word word }
+ words.each { |word| add_stop_word word if !word.empty? }
end
# Add the specified stop word
def add_stop_word( word )
- @stop_words << word unless @stop_words.include? word
+ @stop_words << word.downcase if !@stop_words.include?(word.downcase)
end
# Load stopwords from the specified YAML formatted file
@@ -102,63 +210,52 @@ def load_default_stop_words
load_stop_words( File.join( File.dirname( __FILE__ ), 'stopwords.yml' ) )
end
- # Create a new, empty, pool without training.
- def new_pool( pool_name )
- self.dirty = true
- self.pools[ pool_name ] ||= @data_class.new( pool_name )
- end
-
- def remove_pool( pool_name )
- self.pools.delete( pool_name )
- end
-
- def rename_pool( pool_name, new_name )
- self.pools[new_name] = self.pools[pool_name]
- self.pools[new_name].name = new_name
- self.pools.delete( pool_name )
- self.dirty = true
- end
+ #
+ # EXPORT & IMPORT STATE
+ #
- # Merge the contents of the source pool into the destination
- # destination pool.
- def merge_pools( dest_name, source_name )
- dest_pool = self.pools[dest_name]
- self.pools[source_name].data.each do |token,count|
- if dest_pool.data.has_key?( token )
- dest_pool.data[token] += count
- else
- dest_pool.data[token] = count
- dest_pool.token_count += 1
+ # Get a hash that represents the current state, excluding tokenizer and combiner
+ def export
+ h = {
+ :stop_words => @stop_words.join(',')
+ }
+ pools = {}
+ @pools.each do |pool_name,pool|
+ data = pool.data
+ sorted_data = data.sort do |a,b|
+ if a[1] == b[1]
+ a[0] <=> b[0]
+ else
+ a[1] <=> b[1]
+ end
end
+ pools[pool_name] = {
+ :token_count => pool.token_count,
+ :train_count => pool.train_count,
+ :data => sorted_data.to_h
+ }
end
- self.dirty = true
+ h[:pools] = pools
+ h
end
-
- # Return an array of token counts for the specified pool.
- def pool_data( pool_name )
- self.pools[pool_name].data.to_a
- end
-
- # Return an array of tokens trained in the specified pool.
- def pool_tokens( pool_name )
- self.pools[pool_name].data.keys
+
+ # Gets the current state in YAML format
+ def to_yaml
+ export.to_yaml
end
- # Create a representation of the state of the classifier which can
- # be reloaded later. This does not include the tokenizer, data class,
- # or combiner functions which must be reinitialized each time the
- # classifier is created.
- def save( file = 'bayesdata.yml' )
- File.open( file, 'w' ) { |f| f << export }
+ # Gets the current state in JSON format
+ def to_json
+ JSON.pretty_generate(export)
end
- # Define the YAML representation of the state of the classifier (possibly this
- # should just be an override of the to_yaml method generated by the YAML module).
- def export
- { :pools => self.pools, :train_count => self.train_count, :stop_words => self.stop_words }.to_yaml
+ # Save the current state to a YAML file, default = 'bayesdata.yml'
+ def save_yaml( file = 'bayesdata.yml' )
+ File.open( file, 'w' ) { |f| f << to_yaml }
end
-
- def load( file = 'bayesdata.yml' )
+
+ # Load the current state from a YAML file, default = 'bayesdata.yml'
+ def load_yaml( file = 'bayesdata.yml' )
begin
File.open( file ) { |f| load_data( f ) }
rescue Errno::ENOENT
@@ -166,50 +263,132 @@ def load( file = 'bayesdata.yml' )
end
end
+ #
+ # TRAIN & GUESS
+ #
+
+ # Train the specified pool with the given input.
+ # If the input is a string it is passed through the configured Tokenizer.
+ # Otherwise, if it is an array it is just added.
+ def train( pool_name, input )
+ tokens = input.is_a?(String) ? get_tokens( input ) : input
+ pool = new_pool( pool_name )
+ train_( pool, tokens )
+ pool.train_count += 1
+ @dirty = true
+ end
+
+ # Remove the input from the given pool
+ # If the input is a string it is passed through the configured Tokenizer.
+ # Otherwise, if it is an array it is just added.
+ def untrain( pool_name, input )
+ pool = find_pool( pool_name )
+ return if !pool
+ tokens = input.is_a?(String) ? get_tokens( input ) : input
+ untrain_( pool, tokens )
+ pool.train_count -= 1
+ @dirty = true
+ end
+
+ # Returns true if the specified token has been trained for any pool
+ def trained_on?( token )
+ build_cache if @dirty
+ @cache.values.any? { |v| v.trained_on? token }
+ end
+
+ # Call this method to classify a "message". The return value will be
+ # a hash, with the pool name is the key and the probability is the value, for each pool which
+ # is a likely match for the message.
+ def guess( msg )
+ tokens = get_tokens( msg )
+ res = {}
+
+ build_cache if dirty?
+
+ @cache.each do |pool_name,pool|
+ p = get_probs( pool, tokens )
+ if p.length != 0
+ res[pool_name] = @combiner.call( p, pool_name )
+ end
+ end
+
+ h = Hash.new
+ res.sort.each { |a| h[a[0]] = a[1] }
+ h
+ end
+
+ #
+ # Private Methods
+ #
+
def load_data( source )
data = YAML.load( source )
+ data[:pools].each do |pool_name,pool_data|
+ pool = new_pool(pool_name)
+ pool.train_count = pool_data[:train_count]
+ pool_data[:data].each do |token,value|
+ pool.add_token(token,value)
+ end
+ end
+
+ add_stop_words(data[:stop_words].split(','))
+
+ @dirty = true
+ end
+
+ def dirty? # TODO Make private?
+ @dirty
+ end
+
+ def train_( pool, tokens )
+ tokens.each { |token| pool.add_token(token) }
+ end
+
+ def untrain_( pool, tokens )
+ tokens.each do |token|
+ pool.remove_token(token)
+ end
+ end
+
+ def corpus
+ return @corpus_data if @corpus_data
- @pools = data[:pools]
- @pools.each { |pool_name,pool| pool.data.default = 0.0 }
- @corpus = self.pools['__Corpus__']
+ @corpus_data = BayesPool.new
- @train_count = data[:train_count]
- @stop_words = data[:stop_words]
+ @pools.each do |pool_name, pool|
+ @corpus_data.merge(pool)
+ end
- self.dirty = true
+ @corpus_data
end
- def pool_names
- self.pools.keys.sort.reject { |name| name == '__Corpus__' }
- end
-
# Create a cache of the metrics for each pool.
def build_cache
- self.cache = {}
+ @cache = {}
- self.pools.each do |name,pool|
- unless name == '__Corpus__'
-
- pool_count = pool.token_count
- them_count = [ 1, self.corpus.token_count - pool_count ].max
- cache_dict = self.cache[ name ] ||= @data_class.new( name )
+ return @cache if corpus.token_count == 0.0
+
+ @pools.each do |pool_name,pool|
+ if pool.token_count > 0
+ cache_dict = @cache[ pool_name ] ||= BayesPool.new
- self.corpus.data.each do |token,tot_count|
- this_count = pool.data[token]
+ them_count = [ 1, corpus.token_count - pool.token_count ].max # tokens in other pools
- unless this_count == 0.0
- other_count = tot_count - this_count
+ corpus.data.each do |token,corpus_count|
+ if pool.data.has_key?(token)
- if pool_count > 0
- good_metric = [ 1.0, other_count / pool_count ].min
- else
- good_metric = 1.0
- end
+ # number of references in other pools
+ other_count = corpus_count - pool.data[token]
+
+ # prob token is not in this pool
+ good_metric = [ 1.0, Float(other_count) / Float(pool.token_count) ].min
- bad_metric = [ 1.0, this_count / them_count ].min
+ # prob token is in a different pool
+ # NOTE Must explicitly cast to Floats or else it does integration division, and the result is zero
+ bad_metric = [ 1.0, Float(pool.data[token]) / Float(them_count) ].min
f = bad_metric / ( good_metric + bad_metric )
-
+
if ( f - 0.5 ).abs >= 0.1
cache_dict.data[token] = [ 0.0001, [ 0.9999, f ].min ].max
end
@@ -217,21 +396,13 @@ def build_cache
end
end
end
+ @dirty = false
+ @cache
end
-
- # Get the probabilities for each pool, recreating the cached information if
- # any token information for any of the pools has changed.
- def pool_probs
- if self.dirty?
- self.build_cache
- self.dirty = false
- end
- self.cache
- end
# Create a token array from the specified input.
def get_tokens( input )
- self.tokenizer.tokenize( input, self.stop_words )
+ @tokenizer.tokenize( input, @stop_words )
end
# For each word trained in the pool, collect it's occurrence data in the pool into a sorted array.
@@ -239,87 +410,12 @@ def get_probs( pool, words )
words.find_all { |word| pool.data.has_key? word }.map { |word| [word,pool.data[word]] }.sort
end
- def train( pool_name, item, uid = nil )
- tokens = get_tokens( item )
- pool = new_pool( pool_name )
- train_( pool, tokens )
- self.corpus.train_count += 1
- pool.train_count += 1
- if uid
- pool.training.push( uid )
- end
- self.dirty = true
- end
-
- def train_( pool, tokens )
- wc = 0
- tokens.each do |token|
- pool.data[token] += 1
- self.corpus.data[token] += 1
- wc += 1
- end
- pool.token_count += wc
- self.corpus.token_count += wc
- end
-
- def untrain( pool_name, item, uid = nil )
- tokens = get_tokens( item )
- pool = new_pool( pool_name )
- untrain_( pool, tokens )
- self.corpus.train_count += 1
- pool.train_count += 1
- if uid
- pool.training.delete( uid )
- end
- self.dirty = true
- end
-
- def untrain_( pool, tokens )
- tokens.each do |token|
- if pool.data.has_key? token
- if pool.data[token] == 1
- pool.data.delete( token )
- else
- pool.data[token] -= 1
- end
- pool.token_count -= 1
- end
-
- if self.corpus.data.has_key? token
- if self.corpus.data[token] == 1
- self.corpus.data.delete( token )
- else
- self.corpus.data[token] -= 1
- end
- self.corpus.token_count -= 1
- end
- end
- end
-
- def trained_on?( msg )
- self.cache.values.any? { |v| v.trained_on? msg }
- end
-
- # Call this method to classify a "message". The return value will be
- # an array containing tuples (pool, probability) for each pool which
- # is a likely match for the message.
- def guess( msg )
- tokens = get_tokens( msg )
- res = {}
-
- pool_probs.each do |pool_name,pool|
- p = get_probs( pool, tokens )
- if p.length != 0
- res[pool_name] = self.combiner.call( p, pool_name )
- end
- end
-
- res.sort
- end
+ private :train_, :untrain_, :get_probs, :corpus, :build_cache, :dirty?, :get_tokens, :get_probs, :export, :load_data
- private :train_, :untrain_
end
+ # default "combiner" set in initialize
+ # ignore is truly ignored
def self.robinson( probs, ignore )
nth = 1.0/probs.length
what_is_p = 1.0 - probs.map { |p| 1.0 - p[1] }.inject( 1.0 ) { |s,v| s * v } ** nth
@@ -328,6 +424,7 @@ def self.robinson( probs, ignore )
( 1 + what_is_s ) / 2
end
+ # Alternative combiner
def self.robinson_fisher( probs, ignore )
n = probs.length
@@ -346,7 +443,7 @@ def self.robinson_fisher( probs, ignore )
( 1 + h - s ) / 2
end
- def self.chi2p( chi, df )
+ def self.chi2p( chi, df ) #:nodoc:
m = chi / 2
sum = term = Math.exp( -m )
(1 .. df/2).each do |i|
@@ -355,5 +452,4 @@ def self.chi2p( chi, df )
end
[1.0, sum].min
end
-
end
\ No newline at end of file
diff --git a/test/test_bayes.rb b/test/test_bayes.rb
new file mode 100644
index 0000000..4d71efd
--- /dev/null
+++ b/test/test_bayes.rb
@@ -0,0 +1,206 @@
+require 'rubygems'
+require 'bundler'
+require 'minitest'
+require 'minitest/autorun'
+Bundler.require(:default, :test)
+
+require_relative '../lib/bayes/bishop'
+
+class TestBayes < Minitest::Test
+ parallelize_me!
+
+ LINCOLN1 = "Four score and seven years ago our fathers brought forth on this continent,"+
+ " a new nation, conceived in Liberty, and dedicated to the proposition that all"+
+ " men are created equal."
+ LINCOLN2 ="Now we are engaged in a great civil war, testing whether that nation, "+
+ "or any nation so conceived and so dedicated, can long endure. We are met on"+
+ " a great battle-field of that war. We have come to dedicate a portion of that"+
+ " field, as a final resting place for those who here gave their lives that that"+
+ " nation might live. It is altogether fitting and proper that we should do this."
+ LINCOLN3 = "But, in a larger sense, we can not dedicate -- we can not consecrate -- we can not hallow --"+
+ " this ground. "
+ LINCOLN4 = "The brave men, living and dead, who struggled here, have consecrated it, far above our poor power to add or detract. "
+
+ JABBER1 = "Beware the Jabberwock, my son!"+
+ " The jaws that bite, the claws that catch!"+
+ " Beware the Jubjub bird, and shun The frumious Bandersnatch!"
+ JABBER2 = "He took his vorpal sword in hand:"+
+ " Long time the manxome foe he sought -- " +
+ " So rested he by the Tumtum tree, " +
+ " And stood awhile in thought. "
+ JABBER3 = "And, as in uffish thought he stood, " +
+ " The Jabberwock, with eyes of flame, " +
+ " Came whiffling through the tulgey wood, " +
+ " And burbled as it came!"
+ JABBER4 = "One, two! One, two! And through and through" +
+ " The vorpal blade went snicker-snack! " +
+ " He left it dead, and with its head " +
+ " He went galumphing back."
+
+ ROMEO = "Two households, both alike in dignity, "+
+ "In fair Verona, where we lay our scene, "+
+ "From ancient grudge break to new mutiny, "
+
+ def test_bayes_initializer
+ b = Bishop::Bayes.new
+ assert_instance_of Bishop::SimpleTokenizer, b.tokenizer
+ refute_nil b.combiner
+ assert_equal 0, b.pool_names.length
+ assert_equal 0, b.stop_words.length
+ end
+
+ def test_add_stop_words
+ b = Bishop::Bayes.new
+ sw = %w{ Alpha bEta gammA }
+ assert_equal 0, b.stop_words.length
+ b.add_stop_words( sw )
+ assert_equal 3, b.stop_words.length
+ assert_equal sw.map {|s| s.downcase }, b.stop_words
+ end
+
+ def test_duplicate_stop_words
+ b = Bishop::Bayes.new
+ sw = %w{ Alpha bEta gammA delta epsilon alpha betA omega }
+ sw2 = sw.map { |s| s.downcase }.uniq.sort
+ assert_equal 0, b.stop_words.length
+ b.add_stop_words( sw )
+ assert_equal sw2.length, b.stop_words.length
+ assert_equal sw2, b.stop_words.sort
+ end
+
+ def test_default_stop_words
+ b = Bishop::Bayes.new
+ assert_equal 0, b.stop_words.length
+ b.load_default_stop_words
+ refute_equal 0, b.stop_words.length
+ end
+
+ def test_new_pool
+ b = Bishop::Bayes.new
+ p = b.new_pool('testing')
+ refute_nil b.pool('testing')
+ assert_equal b.pool('testing'),p
+
+ b.remove_pool('testing')
+ assert_nil b.pool('testing')
+ end
+
+ def test_rename_pool
+ b = Bishop::Bayes.new
+ p = b.new_pool('testing')
+ refute_nil b.pool('testing')
+ b.rename_pool('testing','gnitset')
+ assert_nil b.pool('testing')
+ refute_nil b.pool('gnitset')
+ end
+
+ def test_pool_names
+ b = Bishop::Bayes.new
+ names1 = %w{ gamma alpha beta}
+ names1.each { |n| b.new_pool(n) }
+ assert_equal names1.sort, b.pool_names
+ end
+
+ def test_train_simple
+ b = Bishop::Bayes.new
+
+ b.load_default_stop_words
+
+ b.train('lincoln', LINCOLN1)
+ b.train('lincoln', LINCOLN2)
+ b.train('lincoln', LINCOLN3)
+
+ b.train('jabber', JABBER1)
+ b.train('jabber', JABBER2)
+ b.train('jabber', JABBER3)
+
+ guess_lincoln = b.guess(LINCOLN4)
+
+ assert_kind_of Hash, guess_lincoln
+
+ guess_jabber = b.guess(JABBER4)
+
+ guess_romeo = b.guess(ROMEO)
+
+ assert guess_lincoln.has_key?('lincoln')
+ assert guess_jabber.has_key?('jabber')
+ refute guess_romeo.has_key?('lincoln')
+ refute guess_romeo.has_key?('jabber')
+
+ assert guess_lincoln['lincoln'] > 0.9
+ assert guess_jabber['jabber'] > 0.9
+ end
+
+ def test_train_array
+ b = Bishop::Bayes.new
+ t = Bishop::SimpleTokenizer.new
+
+ b.train('a', t.tokenize(LINCOLN1))
+ b.train('a', t.tokenize(LINCOLN2))
+ b.train('a', t.tokenize(LINCOLN3))
+
+ b.train('b', LINCOLN1)
+ b.train('b', LINCOLN2)
+ b.train('b', LINCOLN3)
+
+ assert_equal b.pool('a').data, b.pool('b').data
+ end
+
+ def test_pool_merge
+ b = Bishop::Bayes.new
+
+ b.load_default_stop_words
+
+ b.train('lincoln', LINCOLN1)
+ b.train('lincoln', LINCOLN2)
+ b.train('lincoln', LINCOLN3)
+
+ b.train('jabber', JABBER1)
+ b.train('jabber', JABBER2)
+ b.train('jabber', JABBER3)
+
+ guess = b.guess(LINCOLN4)
+
+ assert guess.has_key?('lincoln')
+ refute guess.has_key?('jabber')
+
+ b.merge_pools('jabber','lincoln')
+
+ guess = b.guess(LINCOLN4)
+
+ assert guess.has_key?('jabber')
+ assert guess.has_key?('lincoln')
+
+
+ end
+
+ def test_to_json
+ b = Bishop::Bayes.new
+
+
+ b.load_default_stop_words
+
+ b.train('lincoln', LINCOLN1)
+ b.train('lincoln', LINCOLN2)
+ b.train('lincoln', LINCOLN3)
+
+ b.train('jabber', JABBER1)
+ b.train('jabber', JABBER2)
+ b.train('jabber', JABBER3)
+
+ b.train('romeo',ROMEO)
+
+ j = JSON.parse(b.to_json)
+
+ assert j.has_key?('stop_words')
+ assert j.has_key?('pools')
+ train_counts = { 'lincoln' => 3, 'jabber' => 3, 'romeo' => 1}
+ ['lincoln','jabber','romeo'].each do |p|
+ assert j['pools'].has_key?(p)
+ assert train_counts[p], j['pools'][p]['train_count']
+ assert_equal j['pools'][p]['token_count'],j['pools'][p]['data'].inject(0) { |sum,n| sum + n[1] }
+ end
+ end
+
+
+end
\ No newline at end of file
diff --git a/test/test_bayes_pool.rb b/test/test_bayes_pool.rb
new file mode 100644
index 0000000..0a0a17c
--- /dev/null
+++ b/test/test_bayes_pool.rb
@@ -0,0 +1,67 @@
+require 'rubygems'
+require 'bundler'
+require 'minitest'
+require 'minitest/autorun'
+Bundler.require(:default, :test)
+
+require_relative '../lib/bayes/bishop'
+
+class TestBayesPool < Minitest::Test
+ parallelize_me!
+
+ LINCOLN1 = "Four score and seven years ago our fathers brought forth on this continent,"+
+ " a new nation, conceived in Liberty, and dedicated to the proposition that all"+
+ " men are created equal."
+
+ def test_creation_simple
+ bp = Bishop::BayesPool.new
+ refute_nil bp
+ refute_nil bp.data
+ assert_equal 0, bp.token_count
+ assert_equal 0, bp.train_count
+ assert_equal "", bp.to_s
+ end
+
+ def test_merge
+ bp = Bishop::BayesPool.new
+ end
+
+ def test_indexing
+ b = Bishop::Bayes.new
+
+ b.train('lincoln', LINCOLN1)
+
+ pool = b.pool('lincoln')
+
+ pool.tokens.each do |token|
+ assert_equal pool.data[token], pool[token]
+ end
+ end
+
+ def test_index_set
+ b = Bishop::Bayes.new
+
+ pool = b.new_pool('simple')
+
+ (1..10).each { |i| pool["token#{i}"] = i}
+
+ (1..10).each do |i|
+ assert_equal i, pool["token#{i}"]
+ end
+ end
+
+ def test_enumerable
+ b = Bishop::Bayes.new
+
+ b.train('lincoln', LINCOLN1)
+
+ pool = b.pool('lincoln')
+
+ pool.each do |k,v|
+ assert_equal pool.data[k],v
+ assert_equal pool[k],v
+ end
+ end
+
+
+end
\ No newline at end of file
diff --git a/test/test_tokenizers.rb b/test/test_tokenizers.rb
new file mode 100644
index 0000000..f07a9fe
--- /dev/null
+++ b/test/test_tokenizers.rb
@@ -0,0 +1,33 @@
+require 'rubygems'
+require 'bundler'
+require 'minitest'
+require 'minitest/autorun'
+Bundler.require(:default, :test)
+
+require_relative '../lib/bayes/bishop'
+
+class TestTokenizers < Minitest::Test
+ parallelize_me!
+
+ def test_simple_tokenizer
+ tokenizer = Bishop::SimpleTokenizer.new
+ s1 = ' this " :-) ;.; % $ &*# is a hyPhen-Test to see - what happens -- '
+ r1 = ["this", "is", "a", "hyphen-test", "to", "see", "what", "happens"]
+ assert_equal r1, tokenizer.tokenize(s1)
+ end
+
+ def test_simple_tokenizer_stop_words
+ tokenizer = Bishop::SimpleTokenizer.new
+ s1 = ' alpha beta delta gamma omega phi psi tau '
+ r1 = %w( alpha beta gamma omega psi tau )
+ assert_equal r1, tokenizer.tokenize(s1,%w(delta phi))
+ end
+
+ def test_stemming_tokenizer
+ tokenizer = Bishop::StemmingTokenizer.new
+ s1 = ' thankfulness liveliness socializer socialism '
+ r1 = %w( thank liveli social social )
+ tokens = tokenizer.tokenize(s1)
+ assert_equal r1, tokens
+ end
+end
\ No newline at end of file
diff --git a/test/test_yaml.rb b/test/test_yaml.rb
new file mode 100644
index 0000000..8333f84
--- /dev/null
+++ b/test/test_yaml.rb
@@ -0,0 +1,40 @@
+require 'rubygems'
+require 'bundler'
+require 'minitest'
+require 'minitest/autorun'
+Bundler.require(:default, :test)
+
+require_relative '../lib/bayes/bishop'
+
+class TestYaml < Minitest::Test
+ parallelize_me!
+
+ LINCOLN1 = "Four score and seven years ago our fathers brought forth on this continent,"+
+ " a new nation, conceived in Liberty, and dedicated to the proposition that all"+
+ " men are created equal."
+
+
+ ROMEO = "Two households, both alike in dignity, "+
+ "In fair Verona, where we lay our scene, "+
+ "From ancient grudge break to new mutiny, "
+
+ def test_yaml
+ b1 = Bishop::Bayes.new
+ b1.add_stop_words(ROMEO.split(/[^\w]+/))
+ b1.train('lincoln',LINCOLN1)
+ b1.save_yaml
+
+ b2 = Bishop::Bayes.new
+ b2.load_yaml
+
+ assert_equal b1.stop_words, b2.stop_words
+
+ b1_pool = b1.pool('lincoln')
+ b2_pool = b2.pool('lincoln')
+ assert_equal b1_pool.train_count, b2_pool.train_count
+ assert_equal b1_pool.token_count, b2_pool.token_count
+ assert_equal b1_pool.data, b2_pool.data
+ end
+
+
+end
\ No newline at end of file