Reference

All functions

AdaBoostClassifier()

Adaboost classifier with quasi-randomized hidden layer

BaseRegressor()

Linear regressor with a quasi-randomized layer

BayesianRVFL2Regressor()

Bayesian Random Vector Functional link network with 2 shrinkage parameters

BayesianRVFLRegressor()

Bayesian Random Vector Functional link network with 1 shrinkage parameter

CustomClassifier()

Custom classifier with quasi-randomized layer

CustomRegressor()

Custom regressor with quasi-randomized layer

DeepClassifier()

Deep classification models

DeepMTS()

Deep MTS models

DeepRegressor()

Deep regression models

GLMClassifier()

Generalized nonlinear models for Classification

GLMRegressor()

Generalized nonlinear models for continuous output (regression)

LazyClassifier()

Automated Machine Learning for classification models

LazyDeepClassifier()

Automated Machine Learning for deep classification models

LazyDeepMTS()

Automated Machine Learning for deep time series models

LazyDeepRegressor()

Automated Machine Learning for deep regression models

LazyMTS()

Automated Machine Learning for time series models

LazyRegressor()

Automated Machine Learning for regression models

MTS()

Multivariate Time Series

MultitaskClassifier()

Multitask Classification model based on regression models, with shared covariates

RandomBagClassifier()

Bootstrap aggregating with quasi-randomized layer (classification)

RandomBagRegressor()

Bootstrap aggregating with quasi-randomized layer (regression)

Ridge2Classifier()

Multinomial logit, quasi-randomized classification model with 2 shrinkage parameters

Ridge2MultitaskClassifier()

Multitask quasi-randomized classification model with 2 shrinkage parameters

Ridge2Regressor()

Quasi-randomized regression model with 2 shrinkage parameters

plot(<MTS>)

Plot multivariate time series forecast or residuals

to_forecast()

Transform list to forecast or mforecast object