classes/candidate_elimination at main · srusti610/classes · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
#Defining Model (Candidate Elimination algorithm concepts)
import numpy as np

import pandas as pd

data = pd.DataFrame(data=pd.read_csv('data.csv'))

print(data)

def learn(concepts, target):

    specific_h = concepts[0].copy()

    print("Initialization of specific_h and general_h")

    print("specific_h: ",specific_h)

    general_h = [["?" for i in range(len(specific_h))] for i in range(len(specific_h))]

    print("general_h: ",general_h)

    print("concepts: ",concepts)

    for i, h in enumerate(concepts):

        if target[i] == "yes":

            for x in range(len(specific_h)):

                #print("h[x]",h[x])

                if h[x] != specific_h[x]:

                    specific_h[x] = '?'

                    general_h[x][x] = '?'

        if target[i] == "no":

            for x in range(len(specific_h)):

                if h[x] != specific_h[x]:

                    general_h[x][x] = specific_h[x]

                else:

                    general_h[x][x] = '?'

    print("\nSteps of Candidate Elimination Algorithm: ",i+1)

    print("Specific_h: ",i+1)

    print(specific_h,"\n")

    print("general_h :", i+1)

    print(general_h)

    indices = [i for i, val in enumerate(general_h) if val == ['?', '?', '?', '?', '?', '?']]

    print("\nIndices",indices)

    for i in indices:

        general_h.remove(['?', '?', '?', '?', '?', '?'])

    return specific_h, general_h

s_final,g_final = learn(concepts, target)

print("\nFinal Specific_h:", s_final, sep="\n")

print("Final General_h:", g_final, sep="\n")