机器学习book
机器学习：使用Python
简介Scikit-learn 机器学习
分类法 Classification
Ex 1: Recognizing hand-written digits
EX 2: Normal and Shrinkage Linear Discriminant Analysis for classification
EX 3: Plot classification probability
EX 4: Classifier Comparison
EX 5: Linear and Quadratic Discriminant Analysis with confidence ellipsoid
特徵选择 Feature Selection
Ex 1: Pipeline Anova SVM
Ex 2: Recursive Feature Elimination
Ex 3: Recursive Feature Elimination with Cross-Validation
Ex 4: Feature Selection using SelectFromModel
Ex 5: Test with permutations the significance of a classification score
Ex 6: Univariate Feature Selection
Ex 7: Comparison of F-test and mutual information
互分解 Cross Decomposition
通用范例 General Examples
Ex 1: Plotting Cross-Validated Predictions
Ex 2: Concatenating multiple feature extraction methods
Ex 3: Isotonic Regression
Ex 4: Imputing missing values before building an estimator
Ex 7: Face completion with a multi-output estimators
群聚法 Clustering
EX 12:Spectral clustering for image segmentation
机器学习资料集 Datasets
Ex 1: The digits 手写数字辨识
Ex 3: The iris 鸢尾花资料集
应用范例 Application
波士顿房地产云端评估(一)
波士顿房地产云端评估(二)
类神经网路 Neural_Networks
Ex 1: Visualization of MLP weights on MNIST
Ex 2: Restricted Boltzmann Machine features for digit classification
Ex 3: Compare Stochastic learning strategies for MLPClassifier
Ex 4: Varying regularization in Multi-layer Perceptron
决策树 Decision_trees
Ex 1: Decision Tree Regression
Ex 2: Multi-output Decision Tree Regression
Ex 3: Plot the decision surface of a decision tree on the iris dataset
Ex 4: Understanding the decision tree structure
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分类法 Classification
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