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機器學習：使用Python
簡介Scikit-learn 機器學習
分類法 Classification
特徵選擇 Feature Selection
互分解 Cross Decomposition
通用範例 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 5: ROC Curve with Visualization API
Ex 7: Face completion with a multi-output estimators
群聚法 Clustering
支持向量機
機器學習資料集 Datasets
應用範例 Application
類神經網路 Neural_Networks
決策樹 Decision_trees
機器學習：使用 NVIDIA JetsonTX2
廣義線性模型 Generalized Linear Models
模型選擇 Model Selection
半監督式分類法 Semi-Supervised Classification
Ensemble_methods
Miscellaneous_examples
Nearest_Neighbors
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通用範例 General Examples
Here are the articles in this section:
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 5: ROC Curve with Visualization API
Ex 7: Face completion with a multi-output estimators
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互分解 Cross Decomposition
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Ex 1: Plotting Cross-Validated Predictions
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