Last Update: 2025-2-15
| ID | Model Name | PyMilo Version |
|---|---|---|
| 1 | Linear Regressor | >=0.1 |
| 2 | Ridge Regressor | >=0.1 |
| 3 | Ridge Classifier | >=0.1 |
| 4 | Ridge Regressor CV | >=0.1 |
| 5 | Ridge Classifier CV | >=0.1 |
| 6 | Lasso | >=0.1 |
| 7 | Lasso CV | >=0.1 |
| 8 | Lasso Lars | >=0.1 |
| 9 | Lasso Lars CV | >=0.1 |
| 10 | Lasso Lars IC | >=0.1 |
| 11 | Multi Task Lasso | >=0.1 |
| 12 | Multi Task Lasso CV | >=0.1 |
| 13 | Elastic Net | >=0.1 |
| 14 | Elastic Net CV | >=0.1 |
| 15 | Multi Task Elastic Net | >=0.1 |
| 16 | Multi Task Elastic Net CV | >=0.1 |
| 17 | Orthogonal Matching Pursuit | >=0.1 |
| 18 | Orthogonal Matching Pursuit CV | >=0.1 |
| 19 | Bayesian Regressor | >=0.1 |
| 20 | Automatic Relevance Determination Regressor | >=0.1 |
| 21 | Logistic Regressor | >=0.1 |
| 22 | Logistic Regressor CV | >=0.1 |
| 23 | Tweedie Regressor | >=0.1 |
| 24 | Poisson Regressor | >=0.1 |
| 25 | Gamma Regressor | >=0.1 |
| 26 | SGD Regressor | >=0.1 |
| 27 | SGD Classifier | >=0.1 |
| 28 | SGD oneclass SVM | >=0.1 |
| 29 | Perceptron | >=0.1 |
| 30 | Passive Aggressive Regressor | >=0.1 |
| 31 | Passive Aggressive Classifier | >=0.1 |
| 32 | OMP | >=0.1 |
| 33 | OMP CV | >=0.1 |
| 34 | Ransac Regressor | >=0.1 |
| 35 | Theil Regressor | >=0.1 |
| 36 | Huber Regressor | >=0.1 |
| 37 | Quantile Regressor | >=0.1 |
| ID | Model Name | PyMilo Version |
|---|---|---|
| 1 | Multi Layer Perceptron Regression | >=0.2 |
| 2 | Multi Layer Perceptron Classifier | >=0.2 |
| 3 | Bernoulli RBM | >=0.2 |
| ID | Model Name | PyMilo Version |
|---|---|---|
| 1 | Decision Tree Regressor | >=0.3 |
| 2 | Decision Tree Classifier | >=0.3 |
| 3 | Extra Tree Regressor | >=0.3 |
| 4 | Extra Tree Classifier | >=0.3 |
| ID | Model Name | PyMilo Version |
|---|---|---|
| 1 | Kmeans | >=0.4 |
| 2 | Bisecting Kmeans | >=0.4 |
| 3 | Mini Batch KMeans | >=0.4 |
| 4 | Affinity Propagation | >=0.4 |
| 5 | Mean Shift | >=0.4 |
| 6 | Spectral Clustering | >=0.4 |
| 7 | Spectral Biclustering | >=0.4 |
| 8 | Spectral Coclustering | >=0.4 |
| 9 | Agglomerative Clustering | >=0.4 |
| 10 | Feature Agglomeration | >=0.4 |
| 11 | DBScan | >=0.4 |
| 12 | HDBScan | >=0.4 |
| 13 | Optics | >=0.4 |
| 14 | Gaussian Mixture | >=0.4 |
| 15 | Bayesian Gaussian Mixture | >=0.4 |
| 16 | Birch | >=0.4 |
| ID | Model Name | PyMilo Version |
|---|---|---|
| 1 | Gaussian Naive Bayes | >=0.5 |
| 2 | Multinomial Naive Bayes | >=0.5 |
| 3 | Bernoulli Naive Bayes | >=0.5 |
| 4 | Complement Naive Bayes | >=0.5 |
| 5 | Categorical Naive Bayes | >=0.5 |
| ID | Model Name | PyMilo Version |
|---|---|---|
| 1 | Linear SVC | >=0.6 |
| 2 | Linear SVR | >=0.6 |
| 3 | NuSVC | >=0.6 |
| 4 | NuSVR | >=0.6 |
| 5 | One Class SVM | >=0.6 |
| 6 | SVC | >=0.6 |
| 7 | SVR | >=0.6 |
| ID | Model Name | PyMilo Version |
|---|---|---|
| 1 | KNeighborsClassifier | >=0.7 |
| 2 | KNeighborsRegressor | >=0.7 |
| 3 | NearestNeighbors | >=0.7 |
| 4 | NearestCentroid | >=0.7 |
| 5 | RadiusNeighborsClassifier | >=0.7 |
| 6 | RadiusNeighborsRegressor | >=0.7 |
| 7 | LocalOutlierFactor | >=0.7 |
| ID | Model Name | PyMilo Version |
|---|---|---|
| 1 | AdaboostClassifier | >=0.8 |
| 2 | AdaboostRegressor | >=0.8 |
| 3 | BaggingClassifier | >=0.8 |
| 4 | BaggingRegressor | >=0.8 |
| 5 | ExtraTreesClassifier | >=0.8 |
| 6 | ExtraTreesRegressor | >=0.8 |
| 7 | GradientBoosterClassifier | >=0.8 |
| 8 | GradientBoosterRegressor | >=0.8 |
| 9 | HistGradientBoostingClassifier | >=0.8 |
| 10 | HistGradientBoostingRegressor | >=0.8 |
| 11 | RandomForestClassifier | >=0.8 |
| 12 | RandomForestRegressor | >=0.8 |
| 13 | StackingClassifier | >=0.8 |
| 14 | StackingRegressor | >=0.8 |
| 15 | VotingClassifier | >=0.8 |
| 16 | VotingRegressor | >=0.8 |
| 17 | IsolationForest | >=0.8 |
| 18 | RandomTreesEmbedding | >=0.8 |
| ID | Model Name | PyMilo Version |
|---|---|---|
| 1 | Pipeline | >=0.8 |
| ID | Model Name | PyMilo Version |
|---|---|---|
| 1 | OneHotEncoder | >=0.8 |
| 2 | LabelBinarizer | >=0.1 |
| 3 | LabelEncoder | >=0.8 |
| 4 | StandardScaler | >=0.8 |
| 5 | Binarizer | >=0.9 |
| 6 | FunctionTransformer | >=0.9 |
| 7 | KernelCenterer | >=0.9 |
| 8 | MultiLabelBinarizer | >=0.9 |
| 9 | MaxAbsScaler | >=0.9 |
| 10 | Normalizer | >=0.9 |
| 11 | OrdinalEncoder | >=0.9 |
| 12 | PolynomialFeatures | >=0.9 |
| 13 | RobustScaler | >=0.9 |
| 14 | QuantileTransformer | >=0.9 |
| 15 | KBinsDiscretizer | >=0.9 |
| 16 | PowerTransformer | >=0.9 |
| 17 | SplineTransformer | >=0.9 |
| 18 | TargetEncoder | >=0.9 |
| ID | Model Name | PyMilo Version |
|---|---|---|
| 1 | PLSRegression | >=1.1 |
| 2 | PLSCanonical | >=1.1 |
| 3 | CCA | >=1.1 |
| ID | Model Name | PyMilo Version |
|---|---|---|
| 1 | DictVectorizer | >=1.3 |
| 2 | FeatureHasher | >=1.3 |
| 3 | PatchExtractor | >=1.3 |
| 4 | CountVectorizer | >=1.3 |
| 5 | HashingVectorizer | >=1.3 |
| 6 | TfidfTransformer | >=1.3 |
| 7 | TfidfVectorizer | >=1.3 |