API Reference

References entry point to classes and method of machinelearn.js; It will give you details on each individual API but it may not explain the full usage to solve problems.

cluster

• cluster.KMeans

datasets

• datasets.Boston

• datasets.HeartDisease

• datasets.Iris

decomposition

• decomposition.PCA

ensemble

• ensemble.BaggingClassifier

• ensemble.RandomForestClassifier

feature_extraction

• feature_extraction.CountVectorizer

linear_model

• linear_model.Lasso

• linear_model.LinearRegression

• linear_model.LogisticRegression

• linear_model.Ridge

• linear_model.SGDClassifier

• linear_model.SGDRegressor

metrics

• metrics.accuracyScore

• metrics.confusion_matrix

• metrics.mean_absolute_error

• metrics.mean_squared_error

• metrics.mean_squared_log_error

• metrics.zeroOneLoss

model_selection

• model_selection.KFold

• model_selection.train_test_split

naive_bayes

• naive_bayes.GaussianNB

• naive_bayes.MultinomialNB

neighbors

• neighbors.KNeighborsClassifier

preprocessing

• preprocessing.Binarizer

• preprocessing.Imputer

• preprocessing.LabelEncoder

• preprocessing.MinMaxScaler

• preprocessing.OneHotEncoder

• preprocessing.PolynomialFeatures

• preprocessing.add_dummy_feature

• preprocessing.normalize

svm

• svm.BaseSVM

• svm.NuSVC

• svm.NuSVR

• svm.OneClassSVM

• svm.SVC

• svm.SVR

tree

• tree.DecisionTreeClassifier