https://github.com/qinhanmin2014/tiny-sklearn

Tiny implementation of important algorithms in scikit-learn. Useful when understanding ML algorithms and scikit-learn.
https://github.com/qinhanmin2014/tiny-sklearn

machine-learning machine-learning-algorithms scikit-learn

Last synced: about 1 year ago
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Tiny implementation of important algorithms in scikit-learn. Useful when understanding ML algorithms and scikit-learn.

• Host: GitHub
• URL: https://github.com/qinhanmin2014/tiny-sklearn
• Owner: qinhanmin2014
• License: mit
• Created: 2019-04-06T08:18:31.000Z (about 7 years ago)
• Default Branch: master
• Last Pushed: 2019-11-22T13:57:56.000Z (over 6 years ago)
• Last Synced: 2025-03-30T22:32:04.135Z (about 1 year ago)
• Topics: machine-learning, machine-learning-algorithms, scikit-learn
• Language: Jupyter Notebook
• Homepage:
• Size: 338 KB
• Stars: 25
• Watchers: 2
• Forks: 3
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# tiny-sklearn

## About

- Tiny implementation of important algorithms in scikit-learn

(e.g., pure python, no input validation, no speed/memory optimization, do not support sparse matrix and multioutput).

- Useful when understanding ML algorithms and scikit-learn.

- Multiple implementations of each algorithm.

- Roughly follow the structure of scikit-learn.

- Roughly follow the API standard of scikit-learn.

- Results are compared with scikit-learn.

## Table of Contents

- **calibration** (sklearn.calibration)

  * [calibration_curve](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/calibration/calibration_curve.ipynb)

  * [CalibratedClassifierCV](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/calibration/CalibratedClassifierCV.ipynb)

- **cluster** (sklearn.cluster)

  * [AgglomerativeClustering](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/cluster/AgglomerativeClustering.ipynb)

  * [DBSCAN](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/cluster/DBSCAN.ipynb)

  * [KMeans](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/cluster/KMeans.ipynb)

- **covariance** (sklearn.covariance)

  * [EmpiricalCovariance](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/covariance/EmpiricalCovariance.ipynb)

- **decomposition** (sklearn.decomposition)

  * [KernelPCA](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/decomposition/KernelPCA.ipynb)

  * [PCA](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/decomposition/PCA.ipynb)

  * [TruncatedSVD](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/decomposition/TruncatedSVD.ipynb)

- **discriminant_analysis** (sklearn.discriminant_analysis)

  * [LinearDiscriminantAnalysis](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/discriminant_analysis/LinearDiscriminantAnalysis.ipynb)

- **dummy** (sklearn.dummy)

  * [DummyClassifier](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/dummy/DummyClassifier.ipynb)

  * [DummyRegressor](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/dummy/DummyRegressor.ipynb)

- **ensemble** (sklearn.ensemble)

  * [AdaBoostClassifier](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/ensemble/AdaBoostClassifier.ipynb)

  * [AdaBoostRegressor](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/ensemble/AdaBoostRegressor.ipynb)

  * [BaggingClassifier](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/ensemble/BaggingClassifier.ipynb)

  * [BaggingRegressor](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/ensemble/BaggingRegressor.ipynb)

  * [GradientBoostingClassifier](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/ensemble/GradientBoostingClassifier.ipynb)

  * [GradientBoostingRegressor](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/ensemble/GradientBoostingRegressor.ipynb)

  * [RandomForestClassifier](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/ensemble/RandomForestClassifier.ipynb)

  * [RandomForestRegressor](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/ensemble/RandomForestRegressor.ipynb)

  * [StackingClassifier](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/ensemble/StackingClassifier.ipynb)

  * [StackingRegressor](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/ensemble/StackingRegressor.ipynb)

  * [VotingClassifier](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/ensemble/VotingClassifier.ipynb)

  * [VotingRegressor](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/ensemble/VotingRegressor.ipynb)

- **feature_extraction** (sklearn.feature_extraction)

  * [CountVectorizer](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/feature_extraction/CountVectorizer.ipynb)

  * [TfidfTransformer](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/feature_extraction/TfidfTransformer.ipynb)

  * [TfidfVectorizer](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/feature_extraction/TfidfVectorizer.ipynb)

- **feature_selection** (sklearn.feature_selection)

  * [RFE](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/feature_selection/RFE.ipynb)

  * [SelectFromModel](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/feature_selection/SelectFromModel.ipynb)

  * [VarianceThreshold](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/feature_selection/VarianceThreshold.ipynb)

- **impute** (sklearn.inpute)

  * [MissingIndicator](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/impute/MissingIndicator.ipynb)

  * [SimpleImputer](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/impute/SimpleImputer.ipynb)

- **inspection** (sklearn.inspection)

  * [partial_dependence](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/inspection/partial_dependence.ipynb)

  * [permutation_importance](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/inspection/permutation_importance.ipynb)

- **kernel_ridge** (sklearn.kernel_ridge)

  * [KernelRidge](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/kernel_ridge/KernelRidge.ipynb)

- **linear_model** (sklearn.linear_model)

  * [LinearRegression](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/linear_model/LinearRegression.ipynb)

  * [LogisticRegression](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/linear_model/LogisticRegression.ipynb)

  * [Ridge](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/linear_model/Ridge.ipynb)

  * [RidgeClassifier](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/linear_model/RidgeClassifier.ipynb)

  * [RidgeCV](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/linear_model/RidgeCV.ipynb)

  * [SGDClassifier](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/linear_model/SGDClassifier.ipynb) 

  * [SGDRegressor](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/linear_model/SGDRegressor.ipynb) 

- **metrics** (sklearn.metrics) - classification metrics

  * [accuracy_score](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/metrics/accuracy_score.ipynb)

  * [average_precision_score](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/metrics/average_precision_score.ipynb)

  * [brier_score_loss](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/metrics/brier_score_loss.ipynb)

  * [confusion_matrix](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/metrics/confusion_matrix.ipynb)

  * [f1_score](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/metrics/f1_score.ipynb)

  * [fbeta_score](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/metrics/fbeta_score.ipynb)

  * [multilabel_confusion_matrix](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/metrics/multilabel_confusion_matrix.ipynb)

  * [precision_recall_curve](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/metrics/precision_recall_curve.ipynb)

  * [precision_score](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/metrics/precision_score.ipynb)

  * [recall_score](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/metrics/recall_score.ipynb)

  * [roc_auc_score](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/metrics/roc_auc_score.ipynb)

  * [roc_curve](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/metrics/roc_curve.ipynb)

- **metrics** (sklearn.metrics) - regression metrics

  * [mean_absolute_error](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/metrics/mean_absolute_error.ipynb)

  * [mean_squared_error](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/metrics/mean_squared_error.ipynb)

  * [median_absolute_error](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/metrics/median_absolute_error.ipynb)

  * [r2_score](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/metrics/r2_score.ipynb)

- **metrics** (sklearn.metrics) - pairwise metrics

  * [cosine_distances](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/metrics/cosine_distances.ipynb)

  * [cosine_similarity](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/metrics/cosine_similarity.ipynb)

  * [euclidean_distances](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/metrics/euclidean_distances.ipynb)

  * [linear_kernel](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/metrics/linear_kernel.ipynb)

  * [rbf_kernel](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/metrics/rbf_kernel.ipynb)

- **mixture** (sklearn.mixture)

  * [GaussianMixture](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/mixture/GaussianMixture.ipynb)

- **neighbors** (sklearn.neighbors)

  * [KNeighborsClassifier](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/neighbors/KNeighborsClassifier.ipynb)

  * [KNeighborsRegressor](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/neighbors/KNeighborsRegressor.ipynb)

  * [NearestCentroid](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/neighbors/NearestCentroid.ipynb)

  * [NearestNeighbors](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/neighbors/NearestNeighbors.ipynb)

  * [RadiusNeighborsClassifier](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/neighbors/RadiusNeighborsClassifier.ipynb)

  * [RadiusNeighborsRegressor](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/neighbors/RadiusNeighborsRegressor.ipynb)

- **model_selection** (sklearn.model_selection) - splitter classes / functions

  * [KFold](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/model_selection/KFold.ipynb)

  * [ShuffleSplit](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/model_selection/ShuffleSplit.ipynb)

  * [StratifiedKFold](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/model_selection/StratifiedKFold.ipynb)

  * [StratifiedShuffleSplit](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/model_selection/StratifiedShuffleSplit.ipynb)

  * [TimeSeriesSplit](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/model_selection/TimeSeriesSplit.ipynb)

  * [train_test_split](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/model_selection/train_test_split.ipynb)

- **model_selection** (sklearn.model_selection) - hyper-parameter optimizers

  * [GridSearchCV](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/model_selection/GridSearchCV.ipynb)

- **model_selection** (sklearn.model_selection) - model validation

  * [cross_val_predict](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/model_selection/cross_val_predict.ipynb)

  * [cross_val_score](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/model_selection/cross_val_score.ipynb)

  * [learning_curve](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/model_selection/learning_curve.ipynb)

  * [validation_curve](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/model_selection/validation_curve.ipynb)

- **multiclass** (sklearn.multiclass)

  * [OneVsOneClassifier](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/multiclass/OneVsOneClassifier.ipynb)

  * [OneVsRestClassifier](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/multiclass/OneVsRestClassifier.ipynb)

  * [OutputCodeClassifier](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/multiclass/OutputCodeClassifier.ipynb)

- **naive_bayes** (sklearn.naive_bayes)

  * [BernoulliNB](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/naive_bayes/BernoulliNB.ipynb)

  * [ComplementNB](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/naive_bayes/ComplementNB.ipynb)

  * [GaussianNB](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/naive_bayes/GaussianNB.ipynb)

  * [MultinomialNB](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/naive_bayes/MultinomialNB.ipynb)

- **neural_network** (sklearn.neural_network)

  * [MLPClassifier](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/neural_network/MLPClassifier.ipynb)

  * [MLPRegressor](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/neural_network/MLPRegressor.ipynb)

- **preprocessing** (sklearn.preprocessing)

  * [Binarizer](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/preprocessing/Binarizer.ipynb)

  * [KBinsDiscretizer](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/preprocessing/KBinsDiscretizer.ipynb)

  * [KernelCenterer](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/preprocessing/KernelCenterer.ipynb)

  * [LabelBinarizer](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/preprocessing/LabelBinarizer.ipynb)

  * [LabelEncoder](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/preprocessing/LabelEncoder.ipynb)

  * [MaxAbsScaler](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/preprocessing/MaxAbsScaler.ipynb)

  * [MinMaxScaler](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/preprocessing/MinMaxScaler.ipynb)

  * [Normalizer](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/preprocessing/Normalizer.ipynb)

  * [RobustScaler](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/preprocessing/RobustScaler.ipynb)

  * [StandardScaler](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/preprocessing/StandardScaler.ipynb)

- **svm** (sklearn.svm)

  * [LinearSVC](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/svm/LinearSVC.ipynb)

  * [SVC](https://nbviewer.jupyter.org/github/qinhanmin2014/Machine-Learning-in-Action/blob/master/06%20Support%20vector%20machines/svmMLiA.ipynb) (difficult to obtain similar results compared with LIBSVM/ scikit-learn)

- **tree** (sklearn.tree)

  * [DecisionTreeClassifier](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/tree/DecisionTreeClassifier.ipynb)

  * [DecisionTreeRegressor](https://nbviewer.jupyter.org/github/qinhanmin2014/tiny-sklearn/blob/master/tree/DecisionTreeRegressor.ipynb)