Machine-Learning/Machine Learning.out at master · hooyuser/Machine-Learning · GitHub

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\BOOKMARK [0][-]{chapter.1}{Introduction}{}% 1
\BOOKMARK [1][-]{section.1.1}{Terminology and Framework}{chapter.1}% 2
\BOOKMARK [1][-]{section.1.2}{Optimal Decision Functions in Special Cases}{chapter.1}% 3
\BOOKMARK [2][-]{subsection.1.2.1}{Loss function for quantitative output variables: squared error loss}{section.1.2}% 4
\BOOKMARK [2][-]{subsection.1.2.2}{Loss function for categorical output variable: 0-1 indicator}{section.1.2}% 5
\BOOKMARK [1][-]{section.1.3}{Generalization Error Bound}{chapter.1}% 6
\BOOKMARK [1][-]{section.1.4}{tradeoff}{chapter.1}% 7
\BOOKMARK [0][-]{chapter.2}{Linear Model}{}% 8
\BOOKMARK [1][-]{section.2.1}{Finite Sample Linear Model}{chapter.2}% 9
\BOOKMARK [2][-]{subsection.2.1.1}{Statistic model setup}{section.2.1}% 10
\BOOKMARK [2][-]{subsection.2.1.2}{Ordinary least square estimate}{section.2.1}% 11
\BOOKMARK [0][-]{chapter.3}{SVM}{}% 12
\BOOKMARK [1][-]{section.3.1}{linear SVM}{chapter.3}% 13
\BOOKMARK [1][-]{section.3.2}{linear SVM}{chapter.3}% 14
\BOOKMARK [0][-]{chapter.4}{KNN}{}% 15
\BOOKMARK [1][-]{section.4.1}{Nearest-neighbor methods}{chapter.4}% 16
\BOOKMARK [0][-]{chapter.5}{Decision Tree}{}% 17
\BOOKMARK [1][-]{section.5.1}{Regression Trees}{chapter.5}% 18
\BOOKMARK [0][-]{chapter.6}{Neural Networks}{}% 19
\BOOKMARK [1][-]{section.6.1}{Single hidden layer back-propagation network}{chapter.6}% 20
\BOOKMARK [2][-]{subsection.6.1.1}{Binary classification}{section.6.1}% 21
\BOOKMARK [2][-]{subsection.6.1.2}{Multi classification}{section.6.1}% 22
\BOOKMARK [1][-]{section.6.2}{Convolutional neural network}{chapter.6}% 23