# ml2json
Export scikit-learn model files to JSON for sharing or deploying predictive models with peace of mind.
This is the continuation of the work hosted at [OlivierBeq/sklearn-json](https://github.com/OlivierBeq/sklearn-json).
# Why ml2json?
Other methods for exporting scikit-learn models require Pickle or Joblib (based on Pickle).
- Serializing model files with Pickle provides a simple attack vector for malicious users - they give an attacker the ability to execute arbitrary code wherever the file is deserialized. For an example see: https://www.smartfile.com/blog/python-pickle-security-problems-and-solutions/.
- Internal designs of Pickle and Joblib files make the binary files not mandatorily supported across Python versions.
ml2json is a safe and transparent solution for exporting scikit-learn model files to text files both machine and human readable.
### Safe
Export model files to 100% JSON which cannot execute code on deserialization.
### Transparent
Model files are serialized in JSON (i.e., not binary), so you have the ability to see exactly what's inside.
# Getting Started
ml2json makes exporting model files to JSON simple.
## Install
```
pip install ml2json
```
To install other all dependencies (e.g. XGBoost, HDBSCAN), use:
```
pip install ml2json[full]
```
## Example Usage
```python
import ml2json
from sklearn.ensemble import RandomForestClassifier
model = RandomForestClassifier(n_estimators=10, max_depth=5, random_state=0).fit(X, y)
ml2json.to_json(model, file_name)
deserialized_model = ml2json.from_json(file_name)
deserialized_model.predict(X)
```
# Features
The list of supported models is rapidly growing.
In addition of the support for scikit-learn models, ml2json supports the following libraries:
- scikit-learn-extra
- XGBoost
- LightGBM
- CatBoost
- Imbalanced-learn
- kmodes
- HDBSCAN
- UMAP
- PyNNDescent
- Prince
- MlChemAD
ml2json requires scikit-learn >= 0.21.3.
## Supported scikit-learn Models
| Library | Category | Class | Supported? |
|:------------------:|:-----------------------------------------:|:---------------------------------------------------:|:------------------:|
| Scikit-Learn | Clustering | cluster.AffinityPropagation | :heavy_check_mark: |
| Scikit-Learn | Clustering | cluster.AgglomerativeClustering | :heavy_check_mark: |
| Scikit-Learn | Clustering | cluster.Birch | :heavy_check_mark: |
| Scikit-Learn | Clustering | cluster.DBSCAN | :heavy_check_mark: |
| Scikit-Learn | Clustering | cluster.FeatureAgglomeration | :heavy_check_mark: |
| Scikit-Learn | Clustering | cluster.KMeans | :heavy_check_mark: |
| Scikit-Learn | Clustering | cluster.BisectingKMeans | :heavy_check_mark: |
| Scikit-Learn | Clustering | cluster.MiniBatchKMeans | :heavy_check_mark: |
| Scikit-Learn | Clustering | cluster.MeanShift | :heavy_check_mark: |
| Scikit-Learn | Clustering | cluster.OPTICS | :heavy_check_mark: |
| Scikit-Learn | Clustering | cluster.SpectralClustering | :heavy_check_mark: |
| Scikit-Learn | Clustering | cluster.SpectralBiclustering | :heavy_check_mark: |
| Scikit-Learn | Clustering | cluster.SpectralCoclustering | :heavy_check_mark: |
| Scikit-Learn | Cross decomposition | cross_decomposition.CCA | :heavy_check_mark: |
| Scikit-Learn | Cross decomposition | cross_decomposition.PLSCanonical | :heavy_check_mark: |
| Scikit-Learn | Cross decomposition | cross_decomposition.PLSRegression | :heavy_check_mark: |
| Scikit-Learn | Cross decomposition | cross_decomposition.PLSSVD | :heavy_check_mark: |
| Scikit-Learn | Decomposition | decomposition.DictionaryLearning | :heavy_check_mark: |
| Scikit-Learn | Decomposition | decomposition.FactorAnalysis | :heavy_check_mark: |
| Scikit-Learn | Decomposition | decomposition.FastICA | :heavy_check_mark: |
| Scikit-Learn | Decomposition | decomposition.IncrementalPCA | :heavy_check_mark: |
| Scikit-Learn | Decomposition | decomposition.KernelPCA | :heavy_check_mark: |
| Scikit-Learn | Decomposition | decomposition.LatentDirichletAllocation | :heavy_check_mark: |
| Scikit-Learn | Decomposition | decomposition.MiniBatchDictionaryLearning | :heavy_check_mark: |
| Scikit-Learn | Decomposition | decomposition.MiniBatchSparsePCA | :heavy_check_mark: |
| Scikit-Learn | Decomposition | decomposition.NMF | :heavy_check_mark: |
| Scikit-Learn | Decomposition | decomposition.MiniBatchNMF | :heavy_check_mark: |
| Scikit-Learn | Decomposition | decomposition.PCA | :heavy_check_mark: |
| Scikit-Learn | Decomposition | decomposition.SparsePCA | :heavy_check_mark: |
| Scikit-Learn | Decomposition | decomposition.SparseCoder | :heavy_check_mark: |
| Scikit-Learn | Decomposition | decomposition.TruncatedSVD | :heavy_check_mark: |
| Scikit-Learn | Discriminant Analysis | discriminant_analysis.LinearDiscriminantAnalysis | :heavy_check_mark: |
| Scikit-Learn | Discriminant Analysis | discriminant_analysis.QuadraticDiscriminantAnalysis | :heavy_check_mark: |
| Scikit-Learn | Ensemble Methods | ensemble.AdaBoostClassifier | :heavy_check_mark: |
| Scikit-Learn | Ensemble Methods | ensemble.AdaBoostRegressor | :heavy_check_mark: |
| Scikit-Learn | Ensemble Methods | ensemble.BaggingClassifier | :heavy_check_mark: |
| Scikit-Learn | Ensemble Methods | ensemble.BaggingRegressor | :heavy_check_mark: |
| Scikit-Learn | Ensemble Methods | ensemble.ExtraTreesClassifier | :heavy_check_mark: |
| Scikit-Learn | Ensemble Methods | ensemble.ExtraTreesRegressor | :heavy_check_mark: |
| Scikit-Learn | Ensemble Methods | ensemble.GradientBoostingClassifier | :heavy_check_mark: |
| Scikit-Learn | Ensemble Methods | ensemble.GradientBoostingRegressor | :heavy_check_mark: |
| Scikit-Learn | Ensemble Methods | ensemble.IsolationForest | :heavy_check_mark: |
| Scikit-Learn | Ensemble Methods | ensemble.RandomForestClassifier | :heavy_check_mark: |
| Scikit-Learn | Ensemble Methods | ensemble.RandomForestRegressor | :heavy_check_mark: |
| Scikit-Learn | Ensemble Methods | ensemble.RandomTreesEmbedding | :heavy_check_mark: |
| Scikit-Learn | Ensemble Methods | ensemble.StackingClassifier | :heavy_check_mark: |
| Scikit-Learn | Ensemble Methods | ensemble.StackingRegressor | :heavy_check_mark: |
| Scikit-Learn | Ensemble Methods | ensemble.VotingClassifier | :heavy_check_mark: |
| Scikit-Learn | Ensemble Methods | ensemble.VotingRegressor | :heavy_check_mark: |
| Scikit-Learn | Ensemble Methods | ensemble.HistGradientBoostingRegressor | :x: |
| Scikit-Learn | Ensemble Methods | ensemble.HistGradientBoostingClassifier | :x: |
| Scikit-Learn | Feature Extraction | feature_extraction.DictVectorizer | :heavy_check_mark: |
| Scikit-Learn | Feature Extraction | feature_extraction.FeatureHasher | :x: |
| Scikit-Learn | Feature Extraction | feature_extraction.image.PatchExtractor | :x: |
| Scikit-Learn | Feature Extraction | feature_extraction.text.CountVectorizer | :x: |
| Scikit-Learn | Feature Extraction | feature_extraction.text.HashingVectorizer | :x: |
| Scikit-Learn | Feature Extraction | feature_extraction.text.TfidfTransformer | :x: |
| Scikit-Learn | Feature Extraction | feature_extraction.text.TfidfVectorizer | :x: |
| Scikit-Learn | Feature Selection | feature_selection.GenericUnivariateSelect | :x: |
| Scikit-Learn | Feature Selection | feature_selection.SelectPercentile | :x: |
| Scikit-Learn | Feature Selection | feature_selection.SelectKBest | :x: |
| Scikit-Learn | Feature Selection | feature_selection.SelectFpr | :x: |
| Scikit-Learn | Feature Selection | feature_selection.SelectFdr | :x: |
| Scikit-Learn | Feature Selection | feature_selection.SelectFromModel | :x: |
| Scikit-Learn | Feature Selection | feature_selection.SelectFwe | :x: |
| Scikit-Learn | Feature Selection | feature_selection.SequentialFeatureSelector | :x: |
| Scikit-Learn | Feature Selection | feature_selection.RFE | :x: |
| Scikit-Learn | Feature Selection | feature_selection.RFECV | :x: |
| Scikit-Learn | Feature Selection | feature_selection.VarianceThreshold | :x: |
| Scikit-Learn | Gaussian Processes | gaussian_process.GaussianProcessClassifier | :x: |
| Scikit-Learn | Gaussian Processes | gaussian_process.GaussianProcessRegressor | :x: |
| Scikit-Learn | Impute | impute.SimpleImputer | :x: |
| Scikit-Learn | Impute | impute.IterativeImputer | :x: |
| Scikit-Learn | Impute | impute.MissingIndicator | :x: |
| Scikit-Learn | Impute | impute.KNNImputer | :x: |
| Scikit-Learn | Isotonic regression | isotonic.IsotonicRegression | :x: |
| Scikit-Learn | Kernel Approximation | kernel_approximation.AdditiveChi2Sampler | :x: |
| Scikit-Learn | Kernel Approximation | kernel_approximation.Nystroem | :x: |
| Scikit-Learn | Kernel Approximation | kernel_approximation.PolynomialCountSketch | :x: |
| Scikit-Learn | Kernel Approximation | kernel_approximation.RBFSampler | :x: |
| Scikit-Learn | Kernel Approximation | kernel_approximation.SkewedChi2Sampler | :x: |
| Scikit-Learn | Kernel Ridge Regression | kernel_ridge.KernelRidge | :x: |
| Scikit-Learn | Linear Models | linear_model.LogisticRegression | :heavy_check_mark: |
| Scikit-Learn | Linear Models | linear_model.LogisticRegressionCV | :x: |
| Scikit-Learn | Linear Models | linear_model.PassiveAggressiveClassifier | :x: |
| Scikit-Learn | Linear Models | linear_model.Perceptron | :heavy_check_mark: |
| Scikit-Learn | Linear Models | linear_model.RidgeClassifier | :x: |
| Scikit-Learn | Linear Models | linear_model.RidgeClassifierCV | :x: |
| Scikit-Learn | Linear Models | linear_model.SGDClassifier | :x: |
| Scikit-Learn | Linear Models | linear_model.SGDOneClassSVM | :x: |
| Scikit-Learn | Linear Models | linear_model.LinearRegression | :heavy_check_mark: |
| Scikit-Learn | Linear Models | linear_model.Ridge | :heavy_check_mark: |
| Scikit-Learn | Linear Models | linear_model.RidgeCV | :x: |
| Scikit-Learn | Linear Models | linear_model.SGDRegressor | :x: |
| Scikit-Learn | Linear Models | linear_model.ElasticNet | :heavy_check_mark: |
| Scikit-Learn | Linear Models | linear_model.ElasticNetCV | :x: |
| Scikit-Learn | Linear Models | linear_model.Lars | :x: |
| Scikit-Learn | Linear Models | linear_model.LarsCV | :x: |
| Scikit-Learn | Linear Models | linear_model.Lasso | :heavy_check_mark: |
| Scikit-Learn | Linear Models | linear_model.LassoCV | :x: |
| Scikit-Learn | Linear Models | linear_model.LassoLars | :x: |
| Scikit-Learn | Linear Models | linear_model.LassoLarsCV | :x: |
| Scikit-Learn | Linear Models | linear_model.LassoLarsIC | :x: |
| Scikit-Learn | Linear Models | linear_model.OrthogonalMatchingPursuit | :x: |
| Scikit-Learn | Linear Models | linear_model.OrthogonalMatchingPursuitCV | :x: |
| Scikit-Learn | Linear Models | linear_model.ARDRegression | :x: |
| Scikit-Learn | Linear Models | linear_model.BayesianRidge | :x: |
| Scikit-Learn | Linear Models | linear_model.MultiTaskElasticNet | :x: |
| Scikit-Learn | Linear Models | linear_model.MultiTaskElasticNetCV | :x: |
| Scikit-Learn | Linear Models | linear_model.MultiTaskLasso | :x: |
| Scikit-Learn | Linear Models | linear_model.MultiTaskLassoCV | :x: |
| Scikit-Learn | Linear Models | linear_model.HuberRegressor | :x: |
| Scikit-Learn | Linear Models | linear_model.QuantileRegressor | :x: |
| Scikit-Learn | Linear Models | linear_model.RANSACRegressor | :x: |
| Scikit-Learn | Linear Models | linear_model.TheilSenRegressor | :x: |
| Scikit-Learn | Linear Models | linear_model.PoissonRegressor | :x: |
| Scikit-Learn | Linear Models | linear_model.TweedieRegressor | :x: |
| Scikit-Learn | Linear Models | linear_model.GammaRegressor | :x: |
| Scikit-Learn | Linear Models | linear_model.PassiveAggressiveRegressor | :x: |
| Scikit-Learn | Manifold Learning | manifold.Isomap | :heavy_check_mark: |
| Scikit-Learn | Manifold Learning | manifold.LocallyLinearEmbedding | :heavy_check_mark: |
| Scikit-Learn | Manifold Learning | manifold.MDS | :heavy_check_mark: |
| Scikit-Learn | Manifold Learning | manifold.SpectralEmbedding | :heavy_check_mark: |
| Scikit-Learn | Manifold Learning | manifold.TSNE | :heavy_check_mark: |
| Scikit-Learn | Gaussian Mixture Models | mixture.BayesianGaussianMixture | :x: |
| Scikit-Learn | Gaussian Mixture Models | mixture.GaussianMixture | :x: |
| Scikit-Learn | Model Selection | model_selection.GroupKFold | :x: |
| Scikit-Learn | Model Selection | model_selection.GroupShuffleSplit | :x: |
| Scikit-Learn | Model Selection | model_selection.KFold | :x: |
| Scikit-Learn | Model Selection | model_selection.LeaveOneGroupOut | :x: |
| Scikit-Learn | Model Selection | model_selection.LeavePGroupsOut | :x: |
| Scikit-Learn | Model Selection | model_selection.LeaveOneOut | :x: |
| Scikit-Learn | Model Selection | model_selection.LeavePOut | :x: |
| Scikit-Learn | Model Selection | model_selection.PredefinedSplit | :x: |
| Scikit-Learn | Model Selection | model_selection.RepeatedKFold | :x: |
| Scikit-Learn | Model Selection | model_selection.RepeatedStratifiedKFold | :x: |
| Scikit-Learn | Model Selection | model_selection.ShuffleSplit | :x: |
| Scikit-Learn | Model Selection | model_selection.StratifiedKFold | :x: |
| Scikit-Learn | Model Selection | model_selection.StratifiedShuffleSplit | :x: |
| Scikit-Learn | Model Selection | model_selection.StratifiedGroupKFold | :x: |
| Scikit-Learn | Model Selection | model_selection.TimeSeriesSplit | :x: |
| Scikit-Learn | Model Selection | model_selection.GridSearchCV | :x: |
| Scikit-Learn | Model Selection | model_selection.HalvingGridSearchCV | :x: |
| Scikit-Learn | Model Selection | model_selection.ParameterGrid | :x: |
| Scikit-Learn | Model Selection | model_selection.ParameterSampler | :x: |
| Scikit-Learn | Model Selection | model_selection.RandomizedSearchCV | :x: |
| Scikit-Learn | Model Selection | model_selection.HalvingRandomSearchCV | :x: |
| Scikit-Learn | Multiclass classification | multiclass.OneVsRestClassifier | :x: |
| Scikit-Learn | Multiclass classification | multiclass.OneVsOneClassifier | :x: |
| Scikit-Learn | Multiclass classification | multiclass.OutputCodeClassifier | :x: |
| Scikit-Learn | Multioutput regression and classification | multioutput.ClassifierChain | :x: |
| Scikit-Learn | Multioutput regression and classification | multioutput.MultiOutputRegressor | :x: |
| Scikit-Learn | Multioutput regression and classification | multioutput.MultiOutputClassifier | :x: |
| Scikit-Learn | Multioutput regression and classification | multioutput.RegressorChain | :x: |
| Scikit-Learn | Naive Bayes | naive_bayes.BernoulliNB | :heavy_check_mark: |
| Scikit-Learn | Naive Bayes | naive_bayes.CategoricalNB | :x: |
| Scikit-Learn | Naive Bayes | naive_bayes.ComplementNB | :heavy_check_mark: |
| Scikit-Learn | Naive Bayes | naive_bayes.GaussianNB | :heavy_check_mark: |
| Scikit-Learn | Naive Bayes | naive_bayes.MultinomialNB | :heavy_check_mark: |
| Scikit-Learn | Nearest Neighbors | neighbors.BallTree | :x: |
| Scikit-Learn | Nearest Neighbors | neighbors.KDTree | :heavy_check_mark: |
| Scikit-Learn | Nearest Neighbors | neighbors.KernelDensity | :heavy_check_mark: |
| Scikit-Learn | Nearest Neighbors | neighbors.KNeighborsClassifier | :heavy_check_mark: |
| Scikit-Learn | Nearest Neighbors | neighbors.KNeighborsRegressor | :heavy_check_mark: |
| Scikit-Learn | Nearest Neighbors | neighbors.KNeighborsTransformer | :x: |
| Scikit-Learn | Nearest Neighbors | neighbors.LocalOutlierFactor | :x: |
| Scikit-Learn | Nearest Neighbors | neighbors.RadiusNeighborsClassifier | :x: |
| Scikit-Learn | Nearest Neighbors | neighbors.RadiusNeighborsRegressor | :x: |
| Scikit-Learn | Nearest Neighbors | neighbors.RadiusNeighborsTransformer | :x: |
| Scikit-Learn | Nearest Neighbors | neighbors.NearestCentroid | :x: |
| Scikit-Learn | Nearest Neighbors | neighbors.NearestNeighbors | :heavy_check_mark: |
| Scikit-Learn | Nearest Neighbors | neighbors.NeighborhoodComponentsAnalysis | :x: |
| Scikit-Learn | Neural network models | neural_network.BernoulliRBM | :x: |
| Scikit-Learn | Neural network models | neural_network.MLPClassifier | :heavy_check_mark: |
| Scikit-Learn | Neural network models | neural_network.MLPRegressor | :heavy_check_mark: |
| Scikit-Learn | Pipeline | pipeline.FeatureUnion | :x: |
| Scikit-Learn | Pipeline | pipeline.Pipeline | :x: |
| Scikit-Learn | Preprocessing and Normalization | preprocessing.Binarizer | :x: |
| Scikit-Learn | Preprocessing and Normalization | preprocessing.FunctionTransformer | :x: |
| Scikit-Learn | Preprocessing and Normalization | preprocessing.KBinsDiscretizer | :x: |
| Scikit-Learn | Preprocessing and Normalization | preprocessing.KernelCenterer | :heavy_check_mark: |
| Scikit-Learn | Preprocessing and Normalization | preprocessing.LabelBinarizer | :heavy_check_mark: |
| Scikit-Learn | Preprocessing and Normalization | preprocessing.LabelEncoder | :heavy_check_mark: |
| Scikit-Learn | Preprocessing and Normalization | preprocessing.MultiLabelBinarizer | :heavy_check_mark: |
| Scikit-Learn | Preprocessing and Normalization | preprocessing.MaxAbsScaler | :heavy_check_mark: |
| Scikit-Learn | Preprocessing and Normalization | preprocessing.MinMaxScaler | :heavy_check_mark: |
| Scikit-Learn | Preprocessing and Normalization | preprocessing.Normalizer | :x: |
| Scikit-Learn | Preprocessing and Normalization | preprocessing.OneHotEncoder | :heavy_check_mark: |
| Scikit-Learn | Preprocessing and Normalization | preprocessing.OrdinalEncoder | :x: |
| Scikit-Learn | Preprocessing and Normalization | preprocessing.PolynomialFeatures | :x: |
| Scikit-Learn | Preprocessing and Normalization | preprocessing.PowerTransformer | :x: |
| Scikit-Learn | Preprocessing and Normalization | preprocessing.QuantileTransformer | :x: |
| Scikit-Learn | Preprocessing and Normalization | preprocessing.RobustScaler | :heavy_check_mark: |
| Scikit-Learn | Preprocessing and Normalization | preprocessing.SplineTransformer | :x: |
| Scikit-Learn | Preprocessing and Normalization | preprocessing.StandardScaler | :heavy_check_mark: |
| Scikit-Learn | Random projection | random_projection.GaussianRandomProjection | :x: |
| Scikit-Learn | Random projection | random_projection.SparseRandomProjection | :x: |
| Scikit-Learn | Semi-Supervised Learning | semi_supervised.LabelPropagation | :x: |
| Scikit-Learn | Semi-Supervised Learning | semi_supervised.LabelSpreading | :x: |
| Scikit-Learn | Semi-Supervised Learning | semi_supervised.SelfTrainingClassifier | :x: |
| Scikit-Learn | Support Vector Machines | svm.LinearSVC | :x: |
| Scikit-Learn | Support Vector Machines | svm.LinearSVR | :x: |
| Scikit-Learn | Support Vector Machines | svm.NuSVC | :x: |
| Scikit-Learn | Support Vector Machines | svm.NuSVR | :x: |
| Scikit-Learn | Support Vector Machines | svm.OneClassSVM | :x: |
| Scikit-Learn | Support Vector Machines | svm.SVC | :heavy_check_mark: |
| Scikit-Learn | Support Vector Machines | svm.SVR | :heavy_check_mark: |
| Scikit-Learn | Decision Trees | tree.DecisionTreeClassifier | :heavy_check_mark: |
| Scikit-Learn | Decision Trees | tree.DecisionTreeRegressor | :heavy_check_mark: |
| Scikit-Learn | Decision Trees | tree.ExtraTreeClassifier | :heavy_check_mark: |
| Scikit-Learn | Decision Trees | tree.ExtraTreeRegressor | :heavy_check_mark: |
| Imbalanced-Learn | Under-sampling | ClusterCentroids | :x: |
| Imbalanced-Learn | Under-sampling | CondensedNearestNeighbour | :x: |
| Imbalanced-Learn | Under-sampling | EditedNearestNeighbours | :x: |
| Imbalanced-Learn | Under-sampling | RepeatedEditedNearestNeighbours | :x: |
| Imbalanced-Learn | Under-sampling | AllKNN | :x: |
| Imbalanced-Learn | Under-sampling | InstanceHardnessThreshold | :x: |
| Imbalanced-Learn | Under-sampling | NearMiss | :x: |
| Imbalanced-Learn | Under-sampling | NeighbourhoodCleaningRule | :x: |
| Imbalanced-Learn | Under-sampling | OneSidedSelection | :x: |
| Imbalanced-Learn | Under-sampling | RandomUnderSampler | :x: |
| Imbalanced-Learn | Under-sampling | TomekLinks | :x: |
| Imbalanced-Learn | Over-sampling | RandomOverSampler | :x: |
| Imbalanced-Learn | Over-sampling | SMOTE | :x: |
| Imbalanced-Learn | Over-sampling | SMOTENC | :x: |
| Imbalanced-Learn | Over-sampling | SMOTEN | :x: |
| Imbalanced-Learn | Over-sampling | ADASYN | :x: |
| Imbalanced-Learn | Over-sampling | BorderlineSMOTE | :x: |
| Imbalanced-Learn | Over-sampling | KMeansSMOTE | :x: |
| Imbalanced-Learn | Over-sampling | SVMSMOTE | :x: |
| Imbalanced-Learn | Combined over & under sampling | SMOTEENN | :x: |
| Imbalanced-Learn | Combined over & under sampling | SMOTETomek | :x: |
| Imbalanced-Learn | Ensemble Methods | EasyEnsembleClassifier | :x: |
| Imbalanced-Learn | Ensemble Methods | RUSBoostClassifier | :x: |
| Imbalanced-Learn | Ensemble Methods | BalancedBaggingClassifier | :x: |
| Imbalanced-Learn | Ensemble Methods | BalancedRandomForestClassifier | :x: |
| XGBoost | Ensemble Methods | XGBRegressor | :heavy_check_mark: |
| XGBoost | Ensemble Methods | XGBClassifier | :heavy_check_mark: |
| XGBoost | Ensemble Methods | XGBRanker | :heavy_check_mark: |
| XGBoost | Ensemble Methods | XGBRFRegressor | :heavy_check_mark: |
| XGBoost | Ensemble Methods | XGBRFClassifier | :heavy_check_mark: |
| LightGBM | Ensemble Methods | LGBMClassifier | :heavy_check_mark: |
| LightGBM | Ensemble Methods | LGBMRegressor | :heavy_check_mark: |
| LightGBM | Ensemble Methods | LGBMRanker | :heavy_check_mark: |
| CatBoost | Ensemble Methods | CatBoostClassifier | :heavy_check_mark: |
| CatBoost | Ensemble Methods | CatBoostRanker | :heavy_check_mark: |
| CatBoost | Ensemble Methods | CatBoostRegressor | :heavy_check_mark: |
| kmodes | Clustering | KModes | :heavy_check_mark: |
| kmodes | Clustering | KPrototypes | :heavy_check_mark: |
| Scikit-Learn-extra | Clustering | cluster.KMedoids | :x: |
| Scikit-Learn-extra | Clustering | cluster.CommonNNClustering | :x: |
| Scikit-Learn-extra | Kernel approximation | kernel_approximation.Fastfood | :x: |
| Scikit-Learn-extra | EigenPro | kernel_methods.EigenProRegressor | :x: |
| Scikit-Learn-extra | Robust | kernel_methods.EigenProClassifier | :x: |
| Scikit-Learn-extra | Robust | robust.RobustWeightedClassifier | :x: |
| Scikit-Learn-extra | Robust | robust.RobustWeightedRegressor | :x: |
| Scikit-Learn-extra | Robust | robust.RobustWeightedKMeans | :x: |
| HDBSCAN | Clustering | HDBSCAN | :heavy_check_mark: |
| UMAP | Manifold Learning | UMAP | :heavy_check_mark: |
| PyNNDescent | Nearest Neighbors | NNDescent | :heavy_check_mark: |
| Prince | Decomposition | PCA | :x: |
| Prince | Decomposition | CA | :x: |
| Prince | Decomposition | MCA | :x: |
| Prince | Decomposition | MFA | :x: |
| Prince | Decomposition | FAMD | :x: |
| Prince | Decomposition | GPA | :x: |
| MLChemAD | Applicability Domain | BoundingBoxApplicabilityDomain | :heavy_check_mark: |
| MLChemAD | Applicability Domain | ConvexHullApplicabilityDomain | :heavy_check_mark: |
| MLChemAD | Applicability Domain | PCABoundingBoxApplicabilityDomain | :heavy_check_mark: |
| MLChemAD | Applicability Domain | TopKatApplicabilityDomain | :heavy_check_mark: |
| MLChemAD | Applicability Domain | LeverageApplicabilityDomain | :heavy_check_mark: |
| MLChemAD | Applicability Domain | HotellingT2ApplicabilityDomain | :heavy_check_mark: |
| MLChemAD | Applicability Domain | KernelDensityApplicabilityDomain | :heavy_check_mark: |
| MLChemAD | Applicability Domain | IsolationForestApplicabilityDomain | :heavy_check_mark: |
| MLChemAD | Applicability Domain | CentroidDistanceApplicabilityDomain | :heavy_check_mark: |
| MLChemAD | Applicability Domain | KNNApplicabilityDomain | :heavy_check_mark: |
| MLChemAD | Applicability Domain | StandardizationApproachApplicabilityDomain | :heavy_check_mark: |
Raw data
{
"_id": null,
"home_page": "https://github.com/OlivierBeq/ml2json",
"name": "ml2json",
"maintainer": "Olivier J.M. B\u00e9quignon",
"docs_url": null,
"requires_python": "",
"maintainer_email": "olivier.bequignon.maintainer@gmail.com",
"keywords": "scikit-learn,serializing,json,reproducibility,machine learning",
"author": "Mathieu Rodrigue",
"author_email": "support@mlrequest.com",
"download_url": "https://files.pythonhosted.org/packages/c6/62/4206b67917de0b881878c23f28d65a2eba962f095446cde296c50664882b/ml2json-0.3.0.tar.gz",
"platform": null,
"description": "# ml2json\r\nExport scikit-learn model files to JSON for sharing or deploying predictive models with peace of mind.\r\n\r\nThis is the continuation of the work hosted at [OlivierBeq/sklearn-json](https://github.com/OlivierBeq/sklearn-json).\r\n\r\n# Why ml2json?\r\nOther methods for exporting scikit-learn models require Pickle or Joblib (based on Pickle).\r\n- Serializing model files with Pickle provides a simple attack vector for malicious users - they give an attacker the ability to execute arbitrary code wherever the file is deserialized. For an example see: https://www.smartfile.com/blog/python-pickle-security-problems-and-solutions/.\r\n- Internal designs of Pickle and Joblib files make the binary files not mandatorily supported across Python versions. \r\n\r\nml2json is a safe and transparent solution for exporting scikit-learn model files to text files both machine and human readable.\r\n\r\n### Safe\r\nExport model files to 100% JSON which cannot execute code on deserialization.\r\n\r\n### Transparent\r\nModel files are serialized in JSON (i.e., not binary), so you have the ability to see exactly what's inside.\r\n\r\n# Getting Started\r\n\r\nml2json makes exporting model files to JSON simple.\r\n\r\n## Install\r\n```\r\npip install ml2json\r\n```\r\n\r\nTo install other all dependencies (e.g. XGBoost, HDBSCAN), use:\r\n\r\n```\r\npip install ml2json[full]\r\n```\r\n## Example Usage\r\n\r\n```python\r\nimport ml2json\r\nfrom sklearn.ensemble import RandomForestClassifier\r\n\r\nmodel = RandomForestClassifier(n_estimators=10, max_depth=5, random_state=0).fit(X, y)\r\n\r\nml2json.to_json(model, file_name)\r\ndeserialized_model = ml2json.from_json(file_name)\r\n\r\ndeserialized_model.predict(X)\r\n```\r\n\r\n# Features\r\nThe list of supported models is rapidly growing.\r\nIn addition of the support for scikit-learn models, ml2json supports the following libraries:\r\n- scikit-learn-extra\r\n- XGBoost\r\n- LightGBM\r\n- CatBoost\r\n- Imbalanced-learn\r\n- kmodes\r\n- HDBSCAN\r\n- UMAP\r\n- PyNNDescent\r\n- Prince\r\n- MlChemAD\r\n\r\nml2json requires scikit-learn >= 0.21.3.\r\n\r\n## Supported scikit-learn Models\r\n\r\n| Library | Category | Class | Supported? |\r\n|:------------------:|:-----------------------------------------:|:---------------------------------------------------:|:------------------:|\r\n| Scikit-Learn | Clustering | cluster.AffinityPropagation | :heavy_check_mark: |\r\n| Scikit-Learn | Clustering | cluster.AgglomerativeClustering | :heavy_check_mark: |\r\n| Scikit-Learn | Clustering | cluster.Birch | :heavy_check_mark: |\r\n| Scikit-Learn | Clustering | cluster.DBSCAN | :heavy_check_mark: |\r\n| Scikit-Learn | Clustering | cluster.FeatureAgglomeration | :heavy_check_mark: |\r\n| Scikit-Learn | Clustering | cluster.KMeans | :heavy_check_mark: |\r\n| Scikit-Learn | Clustering | cluster.BisectingKMeans | :heavy_check_mark: |\r\n| Scikit-Learn | Clustering | cluster.MiniBatchKMeans | :heavy_check_mark: |\r\n| Scikit-Learn | Clustering | cluster.MeanShift | :heavy_check_mark: |\r\n| Scikit-Learn | Clustering | cluster.OPTICS | :heavy_check_mark: |\r\n| Scikit-Learn | Clustering | cluster.SpectralClustering | :heavy_check_mark: |\r\n| Scikit-Learn | Clustering | cluster.SpectralBiclustering | :heavy_check_mark: |\r\n| Scikit-Learn | Clustering | cluster.SpectralCoclustering | :heavy_check_mark: |\r\n| Scikit-Learn | Cross decomposition | cross_decomposition.CCA | :heavy_check_mark: |\r\n| Scikit-Learn | Cross decomposition | cross_decomposition.PLSCanonical | :heavy_check_mark: |\r\n| Scikit-Learn | Cross decomposition | cross_decomposition.PLSRegression | :heavy_check_mark: |\r\n| Scikit-Learn | Cross decomposition | cross_decomposition.PLSSVD | :heavy_check_mark: |\r\n| Scikit-Learn | Decomposition | decomposition.DictionaryLearning | :heavy_check_mark: |\r\n| Scikit-Learn | Decomposition | decomposition.FactorAnalysis | :heavy_check_mark: |\r\n| Scikit-Learn | Decomposition | decomposition.FastICA | :heavy_check_mark: |\r\n| Scikit-Learn | Decomposition | decomposition.IncrementalPCA | :heavy_check_mark: |\r\n| Scikit-Learn | Decomposition | decomposition.KernelPCA | :heavy_check_mark: |\r\n| Scikit-Learn | Decomposition | decomposition.LatentDirichletAllocation | :heavy_check_mark: |\r\n| Scikit-Learn | Decomposition | decomposition.MiniBatchDictionaryLearning | :heavy_check_mark: |\r\n| Scikit-Learn | Decomposition | decomposition.MiniBatchSparsePCA | :heavy_check_mark: |\r\n| Scikit-Learn | Decomposition | decomposition.NMF | :heavy_check_mark: |\r\n| Scikit-Learn | Decomposition | decomposition.MiniBatchNMF | :heavy_check_mark: |\r\n| Scikit-Learn | Decomposition | decomposition.PCA | :heavy_check_mark: |\r\n| Scikit-Learn | Decomposition | decomposition.SparsePCA | :heavy_check_mark: |\r\n| Scikit-Learn | Decomposition | decomposition.SparseCoder | :heavy_check_mark: |\r\n| Scikit-Learn | Decomposition | decomposition.TruncatedSVD | :heavy_check_mark: |\r\n| Scikit-Learn | Discriminant Analysis | discriminant_analysis.LinearDiscriminantAnalysis | :heavy_check_mark: |\r\n| Scikit-Learn | Discriminant Analysis | discriminant_analysis.QuadraticDiscriminantAnalysis | :heavy_check_mark: |\r\n| Scikit-Learn | Ensemble Methods | ensemble.AdaBoostClassifier | :heavy_check_mark: |\r\n| Scikit-Learn | Ensemble Methods | ensemble.AdaBoostRegressor | :heavy_check_mark: |\r\n| Scikit-Learn | Ensemble Methods | ensemble.BaggingClassifier | :heavy_check_mark: |\r\n| Scikit-Learn | Ensemble Methods | ensemble.BaggingRegressor | :heavy_check_mark: |\r\n| Scikit-Learn | Ensemble Methods | ensemble.ExtraTreesClassifier | :heavy_check_mark: |\r\n| Scikit-Learn | Ensemble Methods | ensemble.ExtraTreesRegressor | :heavy_check_mark: |\r\n| Scikit-Learn | Ensemble Methods | ensemble.GradientBoostingClassifier | :heavy_check_mark: |\r\n| Scikit-Learn | Ensemble Methods | ensemble.GradientBoostingRegressor | :heavy_check_mark: |\r\n| Scikit-Learn | Ensemble Methods | ensemble.IsolationForest | :heavy_check_mark: |\r\n| Scikit-Learn | Ensemble Methods | ensemble.RandomForestClassifier | :heavy_check_mark: |\r\n| Scikit-Learn | Ensemble Methods | ensemble.RandomForestRegressor | :heavy_check_mark: |\r\n| Scikit-Learn | Ensemble Methods | ensemble.RandomTreesEmbedding | :heavy_check_mark: |\r\n| Scikit-Learn | Ensemble Methods | ensemble.StackingClassifier | :heavy_check_mark: |\r\n| Scikit-Learn | Ensemble Methods | ensemble.StackingRegressor | :heavy_check_mark: |\r\n| Scikit-Learn | Ensemble Methods | ensemble.VotingClassifier | :heavy_check_mark: |\r\n| Scikit-Learn | Ensemble Methods | ensemble.VotingRegressor | :heavy_check_mark: |\r\n| Scikit-Learn | Ensemble Methods | ensemble.HistGradientBoostingRegressor | :x: |\r\n| Scikit-Learn | Ensemble Methods | ensemble.HistGradientBoostingClassifier | :x: |\r\n| Scikit-Learn | Feature Extraction | feature_extraction.DictVectorizer | :heavy_check_mark: |\r\n| Scikit-Learn | Feature Extraction | feature_extraction.FeatureHasher | :x: |\r\n| Scikit-Learn | Feature Extraction | feature_extraction.image.PatchExtractor | :x: |\r\n| Scikit-Learn | Feature Extraction | feature_extraction.text.CountVectorizer | :x: |\r\n| Scikit-Learn | Feature Extraction | feature_extraction.text.HashingVectorizer | :x: |\r\n| Scikit-Learn | Feature Extraction | feature_extraction.text.TfidfTransformer | :x: |\r\n| Scikit-Learn | Feature Extraction | feature_extraction.text.TfidfVectorizer | :x: |\r\n| Scikit-Learn | Feature Selection | feature_selection.GenericUnivariateSelect | :x: |\r\n| Scikit-Learn | Feature Selection | feature_selection.SelectPercentile | :x: |\r\n| Scikit-Learn | Feature Selection | feature_selection.SelectKBest | :x: |\r\n| Scikit-Learn | Feature Selection | feature_selection.SelectFpr | :x: |\r\n| Scikit-Learn | Feature Selection | feature_selection.SelectFdr | :x: |\r\n| Scikit-Learn | Feature Selection | feature_selection.SelectFromModel | :x: |\r\n| Scikit-Learn | Feature Selection | feature_selection.SelectFwe | :x: |\r\n| Scikit-Learn | Feature Selection | feature_selection.SequentialFeatureSelector | :x: |\r\n| Scikit-Learn | Feature Selection | feature_selection.RFE | :x: |\r\n| Scikit-Learn | Feature Selection | feature_selection.RFECV | :x: |\r\n| Scikit-Learn | Feature Selection | feature_selection.VarianceThreshold | :x: |\r\n| Scikit-Learn | Gaussian Processes | gaussian_process.GaussianProcessClassifier | :x: |\r\n| Scikit-Learn | Gaussian Processes | gaussian_process.GaussianProcessRegressor | :x: |\r\n| Scikit-Learn | Impute | impute.SimpleImputer | :x: |\r\n| Scikit-Learn | Impute | impute.IterativeImputer | :x: |\r\n| Scikit-Learn | Impute | impute.MissingIndicator | :x: |\r\n| Scikit-Learn | Impute | impute.KNNImputer | :x: |\r\n| Scikit-Learn | Isotonic regression | isotonic.IsotonicRegression | :x: |\r\n| Scikit-Learn | Kernel Approximation | kernel_approximation.AdditiveChi2Sampler | :x: |\r\n| Scikit-Learn | Kernel Approximation | kernel_approximation.Nystroem | :x: |\r\n| Scikit-Learn | Kernel Approximation | kernel_approximation.PolynomialCountSketch | :x: |\r\n| Scikit-Learn | Kernel Approximation | kernel_approximation.RBFSampler | :x: |\r\n| Scikit-Learn | Kernel Approximation | kernel_approximation.SkewedChi2Sampler | :x: |\r\n| Scikit-Learn | Kernel Ridge Regression | kernel_ridge.KernelRidge | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.LogisticRegression | :heavy_check_mark: |\r\n| Scikit-Learn | Linear Models | linear_model.LogisticRegressionCV | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.PassiveAggressiveClassifier | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.Perceptron | :heavy_check_mark: |\r\n| Scikit-Learn | Linear Models | linear_model.RidgeClassifier | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.RidgeClassifierCV | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.SGDClassifier | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.SGDOneClassSVM | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.LinearRegression | :heavy_check_mark: |\r\n| Scikit-Learn | Linear Models | linear_model.Ridge | :heavy_check_mark: |\r\n| Scikit-Learn | Linear Models | linear_model.RidgeCV | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.SGDRegressor | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.ElasticNet | :heavy_check_mark: |\r\n| Scikit-Learn | Linear Models | linear_model.ElasticNetCV | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.Lars | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.LarsCV | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.Lasso | :heavy_check_mark: |\r\n| Scikit-Learn | Linear Models | linear_model.LassoCV | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.LassoLars | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.LassoLarsCV | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.LassoLarsIC | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.OrthogonalMatchingPursuit | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.OrthogonalMatchingPursuitCV | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.ARDRegression | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.BayesianRidge | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.MultiTaskElasticNet | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.MultiTaskElasticNetCV | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.MultiTaskLasso | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.MultiTaskLassoCV | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.HuberRegressor | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.QuantileRegressor | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.RANSACRegressor | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.TheilSenRegressor | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.PoissonRegressor | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.TweedieRegressor | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.GammaRegressor | :x: |\r\n| Scikit-Learn | Linear Models | linear_model.PassiveAggressiveRegressor | :x: |\r\n| Scikit-Learn | Manifold Learning | manifold.Isomap | :heavy_check_mark: |\r\n| Scikit-Learn | Manifold Learning | manifold.LocallyLinearEmbedding | :heavy_check_mark: |\r\n| Scikit-Learn | Manifold Learning | manifold.MDS | :heavy_check_mark: |\r\n| Scikit-Learn | Manifold Learning | manifold.SpectralEmbedding | :heavy_check_mark: |\r\n| Scikit-Learn | Manifold Learning | manifold.TSNE | :heavy_check_mark: |\r\n| Scikit-Learn | Gaussian Mixture Models | mixture.BayesianGaussianMixture | :x: |\r\n| Scikit-Learn | Gaussian Mixture Models | mixture.GaussianMixture | :x: |\r\n| Scikit-Learn | Model Selection | model_selection.GroupKFold | :x: |\r\n| Scikit-Learn | Model Selection | model_selection.GroupShuffleSplit | :x: |\r\n| Scikit-Learn | Model Selection | model_selection.KFold | :x: |\r\n| Scikit-Learn | Model Selection | model_selection.LeaveOneGroupOut | :x: |\r\n| Scikit-Learn | Model Selection | model_selection.LeavePGroupsOut | :x: |\r\n| Scikit-Learn | Model Selection | model_selection.LeaveOneOut | :x: |\r\n| Scikit-Learn | Model Selection | model_selection.LeavePOut | :x: |\r\n| Scikit-Learn | Model Selection | model_selection.PredefinedSplit | :x: |\r\n| Scikit-Learn | Model Selection | model_selection.RepeatedKFold | :x: |\r\n| Scikit-Learn | Model Selection | model_selection.RepeatedStratifiedKFold | :x: |\r\n| Scikit-Learn | Model Selection | model_selection.ShuffleSplit | :x: |\r\n| Scikit-Learn | Model Selection | model_selection.StratifiedKFold | :x: |\r\n| Scikit-Learn | Model Selection | model_selection.StratifiedShuffleSplit | :x: |\r\n| Scikit-Learn | Model Selection | model_selection.StratifiedGroupKFold | :x: |\r\n| Scikit-Learn | Model Selection | model_selection.TimeSeriesSplit | :x: |\r\n| Scikit-Learn | Model Selection | model_selection.GridSearchCV | :x: |\r\n| Scikit-Learn | Model Selection | model_selection.HalvingGridSearchCV | :x: |\r\n| Scikit-Learn | Model Selection | model_selection.ParameterGrid | :x: |\r\n| Scikit-Learn | Model Selection | model_selection.ParameterSampler | :x: |\r\n| Scikit-Learn | Model Selection | model_selection.RandomizedSearchCV | :x: |\r\n| Scikit-Learn | Model Selection | model_selection.HalvingRandomSearchCV | :x: |\r\n| Scikit-Learn | Multiclass classification | multiclass.OneVsRestClassifier | :x: |\r\n| Scikit-Learn | Multiclass classification | multiclass.OneVsOneClassifier | :x: |\r\n| Scikit-Learn | Multiclass classification | multiclass.OutputCodeClassifier | :x: |\r\n| Scikit-Learn | Multioutput regression and classification | multioutput.ClassifierChain | :x: |\r\n| Scikit-Learn | Multioutput regression and classification | multioutput.MultiOutputRegressor | :x: |\r\n| Scikit-Learn | Multioutput regression and classification | multioutput.MultiOutputClassifier | :x: |\r\n| Scikit-Learn | Multioutput regression and classification | multioutput.RegressorChain | :x: |\r\n| Scikit-Learn | Naive Bayes | naive_bayes.BernoulliNB | :heavy_check_mark: |\r\n| Scikit-Learn | Naive Bayes | naive_bayes.CategoricalNB | :x: |\r\n| Scikit-Learn | Naive Bayes | naive_bayes.ComplementNB | :heavy_check_mark: |\r\n| Scikit-Learn | Naive Bayes | naive_bayes.GaussianNB | :heavy_check_mark: |\r\n| Scikit-Learn | Naive Bayes | naive_bayes.MultinomialNB | :heavy_check_mark: |\r\n| Scikit-Learn | Nearest Neighbors | neighbors.BallTree | :x: |\r\n| Scikit-Learn | Nearest Neighbors | neighbors.KDTree | :heavy_check_mark: |\r\n| Scikit-Learn | Nearest Neighbors | neighbors.KernelDensity | :heavy_check_mark: |\r\n| Scikit-Learn | Nearest Neighbors | neighbors.KNeighborsClassifier | :heavy_check_mark: |\r\n| Scikit-Learn | Nearest Neighbors | neighbors.KNeighborsRegressor | :heavy_check_mark: |\r\n| Scikit-Learn | Nearest Neighbors | neighbors.KNeighborsTransformer | :x: |\r\n| Scikit-Learn | Nearest Neighbors | neighbors.LocalOutlierFactor | :x: |\r\n| Scikit-Learn | Nearest Neighbors | neighbors.RadiusNeighborsClassifier | :x: |\r\n| Scikit-Learn | Nearest Neighbors | neighbors.RadiusNeighborsRegressor | :x: |\r\n| Scikit-Learn | Nearest Neighbors | neighbors.RadiusNeighborsTransformer | :x: |\r\n| Scikit-Learn | Nearest Neighbors | neighbors.NearestCentroid | :x: |\r\n| Scikit-Learn | Nearest Neighbors | neighbors.NearestNeighbors | :heavy_check_mark: |\r\n| Scikit-Learn | Nearest Neighbors | neighbors.NeighborhoodComponentsAnalysis | :x: |\r\n| Scikit-Learn | Neural network models | neural_network.BernoulliRBM | :x: |\r\n| Scikit-Learn | Neural network models | neural_network.MLPClassifier | :heavy_check_mark: |\r\n| Scikit-Learn | Neural network models | neural_network.MLPRegressor | :heavy_check_mark: |\r\n| Scikit-Learn | Pipeline | pipeline.FeatureUnion | :x: |\r\n| Scikit-Learn | Pipeline | pipeline.Pipeline | :x: |\r\n| Scikit-Learn | Preprocessing and Normalization | preprocessing.Binarizer | :x: |\r\n| Scikit-Learn | Preprocessing and Normalization | preprocessing.FunctionTransformer | :x: |\r\n| Scikit-Learn | Preprocessing and Normalization | preprocessing.KBinsDiscretizer | :x: |\r\n| Scikit-Learn | Preprocessing and Normalization | preprocessing.KernelCenterer | :heavy_check_mark: |\r\n| Scikit-Learn | Preprocessing and Normalization | preprocessing.LabelBinarizer | :heavy_check_mark: |\r\n| Scikit-Learn | Preprocessing and Normalization | preprocessing.LabelEncoder | :heavy_check_mark: |\r\n| Scikit-Learn | Preprocessing and Normalization | preprocessing.MultiLabelBinarizer | :heavy_check_mark: |\r\n| Scikit-Learn | Preprocessing and Normalization | preprocessing.MaxAbsScaler | :heavy_check_mark: |\r\n| Scikit-Learn | Preprocessing and Normalization | preprocessing.MinMaxScaler | :heavy_check_mark: |\r\n| Scikit-Learn | Preprocessing and Normalization | preprocessing.Normalizer | :x: |\r\n| Scikit-Learn | Preprocessing and Normalization | preprocessing.OneHotEncoder | :heavy_check_mark: |\r\n| Scikit-Learn | Preprocessing and Normalization | preprocessing.OrdinalEncoder | :x: |\r\n| Scikit-Learn | Preprocessing and Normalization | preprocessing.PolynomialFeatures | :x: |\r\n| Scikit-Learn | Preprocessing and Normalization | preprocessing.PowerTransformer | :x: |\r\n| Scikit-Learn | Preprocessing and Normalization | preprocessing.QuantileTransformer | :x: |\r\n| Scikit-Learn | Preprocessing and Normalization | preprocessing.RobustScaler | :heavy_check_mark: |\r\n| Scikit-Learn | Preprocessing and Normalization | preprocessing.SplineTransformer | :x: |\r\n| Scikit-Learn | Preprocessing and Normalization | preprocessing.StandardScaler | :heavy_check_mark: |\r\n| Scikit-Learn | Random projection | random_projection.GaussianRandomProjection | :x: |\r\n| Scikit-Learn | Random projection | random_projection.SparseRandomProjection | :x: |\r\n| Scikit-Learn | Semi-Supervised Learning | semi_supervised.LabelPropagation | :x: |\r\n| Scikit-Learn | Semi-Supervised Learning | semi_supervised.LabelSpreading | :x: |\r\n| Scikit-Learn | Semi-Supervised Learning | semi_supervised.SelfTrainingClassifier | :x: |\r\n| Scikit-Learn | Support Vector Machines | svm.LinearSVC | :x: |\r\n| Scikit-Learn | Support Vector Machines | svm.LinearSVR | :x: |\r\n| Scikit-Learn | Support Vector Machines | svm.NuSVC | :x: |\r\n| Scikit-Learn | Support Vector Machines | svm.NuSVR | :x: |\r\n| Scikit-Learn | Support Vector Machines | svm.OneClassSVM | :x: |\r\n| Scikit-Learn | Support Vector Machines | svm.SVC | :heavy_check_mark: |\r\n| Scikit-Learn | Support Vector Machines | svm.SVR | :heavy_check_mark: |\r\n| Scikit-Learn | Decision Trees | tree.DecisionTreeClassifier | :heavy_check_mark: |\r\n| Scikit-Learn | Decision Trees | tree.DecisionTreeRegressor | :heavy_check_mark: |\r\n| Scikit-Learn | Decision Trees | tree.ExtraTreeClassifier | :heavy_check_mark: |\r\n| Scikit-Learn | Decision Trees | tree.ExtraTreeRegressor | :heavy_check_mark: |\r\n| Imbalanced-Learn | Under-sampling | ClusterCentroids | :x: |\r\n| Imbalanced-Learn | Under-sampling | CondensedNearestNeighbour | :x: |\r\n| Imbalanced-Learn | Under-sampling | EditedNearestNeighbours | :x: |\r\n| Imbalanced-Learn | Under-sampling | RepeatedEditedNearestNeighbours | :x: |\r\n| Imbalanced-Learn | Under-sampling | AllKNN | :x: |\r\n| Imbalanced-Learn | Under-sampling | InstanceHardnessThreshold | :x: |\r\n| Imbalanced-Learn | Under-sampling | NearMiss | :x: |\r\n| Imbalanced-Learn | Under-sampling | NeighbourhoodCleaningRule | :x: |\r\n| Imbalanced-Learn | Under-sampling | OneSidedSelection | :x: |\r\n| Imbalanced-Learn | Under-sampling | RandomUnderSampler | :x: |\r\n| Imbalanced-Learn | Under-sampling | TomekLinks | :x: |\r\n| Imbalanced-Learn | Over-sampling | RandomOverSampler | :x: |\r\n| Imbalanced-Learn | Over-sampling | SMOTE | :x: |\r\n| Imbalanced-Learn | Over-sampling | SMOTENC | :x: |\r\n| Imbalanced-Learn | Over-sampling | SMOTEN | :x: |\r\n| Imbalanced-Learn | Over-sampling | ADASYN | :x: |\r\n| Imbalanced-Learn | Over-sampling | BorderlineSMOTE | :x: |\r\n| Imbalanced-Learn | Over-sampling | KMeansSMOTE | :x: |\r\n| Imbalanced-Learn | Over-sampling | SVMSMOTE | :x: |\r\n| Imbalanced-Learn | Combined over & under sampling | SMOTEENN | :x: |\r\n| Imbalanced-Learn | Combined over & under sampling | SMOTETomek | :x: |\r\n| Imbalanced-Learn | Ensemble Methods | EasyEnsembleClassifier | :x: |\r\n| Imbalanced-Learn | Ensemble Methods | RUSBoostClassifier | :x: |\r\n| Imbalanced-Learn | Ensemble Methods | BalancedBaggingClassifier | :x: |\r\n| Imbalanced-Learn | Ensemble Methods | BalancedRandomForestClassifier | :x: |\r\n| XGBoost | Ensemble Methods | XGBRegressor | :heavy_check_mark: |\r\n| XGBoost | Ensemble Methods | XGBClassifier | :heavy_check_mark: |\r\n| XGBoost | Ensemble Methods | XGBRanker | :heavy_check_mark: |\r\n| XGBoost | Ensemble Methods | XGBRFRegressor | :heavy_check_mark: |\r\n| XGBoost | Ensemble Methods | XGBRFClassifier | :heavy_check_mark: |\r\n| LightGBM | Ensemble Methods | LGBMClassifier | :heavy_check_mark: |\r\n| LightGBM | Ensemble Methods | LGBMRegressor | :heavy_check_mark: |\r\n| LightGBM | Ensemble Methods | LGBMRanker | :heavy_check_mark: |\r\n| CatBoost | Ensemble Methods | CatBoostClassifier | :heavy_check_mark: |\r\n| CatBoost | Ensemble Methods | CatBoostRanker | :heavy_check_mark: |\r\n| CatBoost | Ensemble Methods | CatBoostRegressor | :heavy_check_mark: |\r\n| kmodes | Clustering | KModes | :heavy_check_mark: |\r\n| kmodes | Clustering | KPrototypes | :heavy_check_mark: |\r\n| Scikit-Learn-extra | Clustering | cluster.KMedoids | :x: |\r\n| Scikit-Learn-extra | Clustering | cluster.CommonNNClustering | :x: |\r\n| Scikit-Learn-extra | Kernel approximation | kernel_approximation.Fastfood | :x: |\r\n| Scikit-Learn-extra | EigenPro | kernel_methods.EigenProRegressor | :x: |\r\n| Scikit-Learn-extra | Robust | kernel_methods.EigenProClassifier | :x: |\r\n| Scikit-Learn-extra | Robust | robust.RobustWeightedClassifier | :x: |\r\n| Scikit-Learn-extra | Robust | robust.RobustWeightedRegressor | :x: |\r\n| Scikit-Learn-extra | Robust | robust.RobustWeightedKMeans | :x: |\r\n| HDBSCAN | Clustering | HDBSCAN | :heavy_check_mark: |\r\n| UMAP | Manifold Learning | UMAP | :heavy_check_mark: |\r\n| PyNNDescent | Nearest Neighbors | NNDescent | :heavy_check_mark: |\r\n| Prince 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