38 Support Vector Machines1
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29 谱聚类1
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28 Fisher判别分析
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11 - 1 - Linear Models for Binary Classification (21-35)
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8 - 4 - Weighted Classification (16-54)
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32 Computational Methods2
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42 Boosting2
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13 Jacobian
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38 EM算法3
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40 SVM
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20 MDS方法
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31 Computational Methods1
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14 主元分析
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25 spectral clustering
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1 基本概念
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17 概率PCA
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37 Naive Bayes方法
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Enterprise Architect官网教程1-入门
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35 Linear classification1
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15 Wishart 分布
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41 Boosting1
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2 - 1 - Perceptron Hypothesis Set (15-42)
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11 - 3 - Multiclass via Logistic Regression (14-18)
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18 最大似然估计方法
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15 - 1 - Model Selection Problem (16-00)
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13 核主元分析
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01 概率基础
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10 - 4 - Gradient Descent (19-18)(1)
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12 正定核应用
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6 - 4 - A Pictorial Proof (16-01)
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7 多项式分布
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6 - 3 - Bounding Function- Inductive Cases (14-47)
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36 Linear classification2
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12 - 4 - Structured Hypothesis Sets (09-36)
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15 - 2 - Validation (13-24)
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14 - 4 - General Regularizers (13-28)
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16 - 3 - Data Snooping (12-28)
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41 Markov Chain Monte carlo2
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8 - 3 - Algorithmic Error Measure (13-46)
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10 - 3 - Gradient of Logistic Regression Error (15-38)
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15 主坐标分析