SUPPORTED_MODELS.md

Supported Models

Last Update: 2024-05-30

Scikit-Learn

Linear Models

📚 Models Document

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

Neural Networks

📚 Models Document

ID	Model Name	PyMilo Version
1	Multi Layer Perceptron Regression	>=0.2
2	Multi Layer Perceptron Classifier	>=0.2
3	Bernoulli RBM	>=0.2

Decision Trees

📚 Models Document

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

Clustering Models

📚 Models Document

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

Naive Bayes

📚 Models Document

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

Support Vector Machine

📚 Models Document

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

Neighbors

📚 Models Document

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

Ensemble

📚 Models Document

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

Pipeline

📚 Models Document

ID	Model Name	PyMilo Version
1	Pipeline	>=0.8

Preprocessing Modules

📚 Models Document

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