├── Books ├── 《机器学习》西瓜书训练营作业（第十期）.docx ├── 《机器学习》西瓜书训练营作业（第十期）.pdf └── 机器学习-西瓜书笔记汇总.pdf ├── Note ├── images │ ├── 10-1-KNN.png │ ├── 10-2-The-Range-of-Coefficient-K.png │ ├── 10-3-Isomap.png │ ├── 10-4-LLE.png │ ├── 11-1-The-Decline-Speed-of-L1-and-L2.png │ ├── 11-2-Spatial-Constraints-of-L1-and-L2.png │ ├── 12-1-Linear-Partition-on-Two-Dimensional-Real-Plane.png │ ├── 13-1-Semi-Supervised-Learning.png │ ├── 13-2-Active-Learning-Pure-Semi-Supervised-Learning-and-Direct-Learning.png │ ├── 13-3-Combined-Training.png │ ├── 14-1-State-Variables-and-Observation-Variables.png │ ├── 14-2-Separating-Set.png │ ├── 14-3-Chain-CRF.png │ ├── 14-4-Variable-Elimination-Method-and-Message-Passing-Process.png │ ├── 14-5-Belief-Propagation-Algorithm.png │ ├── 14-6-LDA.png │ ├── 15-1-Reinforcement-Learning.png │ ├── 15-2-Monte-Carlo-Search-Tree.png │ ├── 15-3-Adjustment-of-Valuation-Function.png │ ├── 2-1-Over-Fit-and-Under-Fit.png │ ├── 2-10-Common-Critical-Values-of-Bilateral-T-Test.png │ ├── 2-11-Two-Learner-Classification-Difference.png │ ├── 2-12-Algorithmic-Comparison-Ordinal-Table.png │ ├── 2-13-Common-Critical-Values-of-F-Test.png │ ├── 2-14-Common-Q-A-Values-of-Nemenyi-Test.png │ ├── 2-15-Generalization-Error-and-Bias-and-Variance.png │ ├── 2-2-10-Fold-Ccross-Validation.png │ ├── 2-3-Classification-Result-Obfuscation-Matrix.png │ ├── 2-4-Confusion-Matrix-Form-of-Binary-Classification.png │ ├── 2-5-P-R-Curve-and-Balance-Point.png │ ├── 2-6-ROC-and-AUC.png │ ├── 2-7-Bicategorized-Cost-Matrix.png │ ├── 2-8-Cost-Curve-and-Expected-Total-Cost.png │ ├── 2-9-T-Distribution.png │ ├── 3-1-Log-Linear-Regression.png │ ├── 3-2-Unit-Step-Function-and-Logistic-Function.png │ ├── 3-3-LDA.png │ ├── 3-4-OvO-and-OvR.png │ ├── 3-5-ECOC-Coding.png │ ├── 4-1-Girls'picking-Process.png │ ├── 4-2-Unpruned-Decision-Tree.png │ ├── 4-3-Prepruning-Decision-Tree.png │ ├── 4-4-Post-Pruning-Decision-Tree.png │ ├── 5-1-Neuron.png │ ├── 5-2-M-P-Neuron-Model.png │ ├── 5-3-Typical-Neuron-Activation-Function.png │ ├── 5-4-Simple-Perceptron.png │ ├── 5-5-Multi-Layer-Neural-Network.png │ ├── 5-6-Multi-Layer-Feed-Forward-Neural-Network.png │ ├── 5-7-BP-Network.png │ ├── 5-8-Global-Minimum-and-Local-Minimum.png │ ├── 5-9-CNN-for-Handwritten-Number-Recognition.png │ ├── 6-1-Hyperplane.png │ ├── 6-2-Gap.png │ ├── 6-3-Support-Vector-and-Margin.png │ ├── 6-4-Common-Kernel-Functions.png │ ├── 6-5-Noise-Data.png │ ├── 7-1-Jensen's-Inequality-for-Convex-Function.png │ ├── 7-2-Coordinate-Descent.png │ ├── 8-1-Ensemble-Learning.png │ ├── 8-2-Ensembled-Individuals.png │ ├── 8-3-Impact-of-Integration-Scale-on-Random-Forest-and-Bagging.png │ └── 9-1-DBSCAN-Definition.png ├── markdown │ ├── 01-绪论.md │ ├── 02-模型的评估与选择.md │ ├── 03-线性模型.md │ ├── 04-决策树.md │ ├── 05-神经网络.md │ ├── 06-支持向量机.md │ ├── 07-贝叶斯分类器.md │ ├── 08-集成学习.md │ ├── 09-聚类.md │ ├── 10-降维与度量学习.md │ ├── 11-特征选择与稀疏学习.md │ ├── 12-计算学习理论.md │ ├── 13-半监督学习.md │ ├── 14-概率图模型.md │ └── 15-强化学习.md └── notebook │ ├── 00-机器学习-西瓜书笔记汇总.ipynb │ ├── 01-绪论.ipynb │ ├── 02-模型的评估与选择.ipynb │ ├── 03-线性模型.ipynb │ ├── 04-决策树.ipynb │ ├── 05-神经网络.ipynb │ ├── 06-支持向量机.ipynb │ ├── 07-贝叶斯分类器.ipynb │ ├── 08-集成学习.ipynb │ ├── 09-聚类.ipynb │ ├── 10-降维与度量学习.ipynb │ ├── 11-特征选择与稀疏学习.ipynb │ ├── 12-计算学习理论.ipynb │ ├── 13-半监督学习.ipynb │ ├── 14-概率图模型.ipynb │ └── 15-强化学习.ipynb ├── README.md ├── Week1 ├── MyHomeWork │ ├── homework_1.md │ ├── homework_2.py │ ├── homework_3.md │ └── result.csv └── Reference-Material │ ├── plot_logistic_l1_l2_sparsity.ipynb │ ├── plot_logistic_multinomial.ipynb │ ├── plot_logistic_path.ipynb │ ├── plot_sparse_logistic_regression_20newsgroups.ipynb │ └── plot_sparse_logistic_regression_mnist.ipynb ├── Week10 └── MyHomeWork │ ├── plot_kmeans_assumptions.ipynb │ └── plot_kmeans_assumptions.py ├── Week2 └── MyHomeWork │ ├── plot_sparse_logistic_regression_mnist.ipynb │ └── plot_sparse_logistic_regression_mnist.py ├── Week3 └── MyHomeWork │ ├── plot_iris_dtc.ipynb │ └── plot_iris_dtc.py ├── Week4 └── MyHomeWork │ ├── plot_iris_svc.ipynb │ └── plot_iris_svc.py ├── Week5 └── MyHomeWork │ ├── iris_gaussian_naive_bayes.ipynb │ └── iris_gaussian_naive_bayes.py ├── Week6 └── MyHomeWork │ ├── plot_mnist_filters.ipynb │ └── plot_mnist_filters.py ├── Week7 └── MyHomeWork │ ├── plot_roc_crossval.ipynb │ └── plot_roc_crossval.py ├── Week8 └── MyHomeWork │ ├── plot_feature_selection.ipynb │ └── plot_feature_selection.py └── Week9 └── MyHomeWork ├── lightGBM-Example.ipynb ├── lightGBM-Example.py ├── model.txt ├── regression.test └── regression.train /Books/《机器学习》西瓜书训练营作业（第十期）.docx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Relph1119/MachineLearning-WatermelonBook/HEAD/Books/《机器学习》西瓜书训练营作业（第十期）.docx -------------------------------------------------------------------------------- /Books/《机器学习》西瓜书训练营作业（第十期）.pdf: -------------------------------------------------------------------------------- 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