15 - 1 - Model Selection Problem (16-00)
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28 Fisher判别分析
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15 主坐标分析
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41 Boosting1
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13 Jacobian
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40 SVM
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15 - 4 - V-Fold Cross Validation (10-41)
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17 概率PCA
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26 K-means algorithm
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16 - 1 - Occam-'s Razor (10-08)
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01 概率基础
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16 - 3 - Data Snooping (12-28)
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15 - 2 - Validation (13-24)
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34 Kernel FDA
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1 基本概念
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14 - 1 - Regularized Hypothesis Set (19-16)
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16 - 2 - Sampling Bias (11-50)
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6 - 4 - A Pictorial Proof (16-01)
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18 最大似然估计方法
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20 MDS方法
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14 - 2 - Weight Decay Regularization (24-08)
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37 Naive Bayes方法
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25 spectral clustering
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39 Support Vector Machines2
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11 - 1 - Linear Models for Binary Classification (21-35)
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12 - 3 - Price of Nonlinear Transform (15-37)
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1 - 2 - What is Machine Learning (18-28)
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9 - 3 - Generalization Issue (20-34)
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8 - 1 - Noise and Probabilistic Target (17-01)
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15 Wishart 分布
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5 - 2 - Effective Number of Lines (15-26)
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10 - 3 - Gradient of Logistic Regression Error (15-38)
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14 - 4 - General Regularizers (13-28)
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32 随机投影
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6 条件期望
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14 主元分析
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8 多元高斯分布及应用
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2 随机向量
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5 - 3 - Effective Number of Hypotheses (16-17)
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34 Stochastic Convergence-性质
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11 正定核性质