train_models: Train models from given engines

In ModelOriented/forester: Quick and Simple Tools for Training and Testing of Tree-Based Models

Train models from given engines

Description

Train models from given engines

Usage

train_models(data, y = NULL, time = NULL, status = NULL, engine, type)

Arguments

data	A training data for models created by 'prepare_data()' function.
y	A string that indicates a target column name for regression or classification. Either y, or pair: time, status can be used. By default NULL.
time	A string that indicates a time column name for survival analysis task. Either y, or pair: time, status can be used. By default NULL.
status	A string that indicates a status column name for survival analysis task. Either y, or pair: time, status can be used. By default NULL.
engine	A vector of tree-based models that shall be created. Possible values are: ‘ranger', 'xgboost','decision_tree', 'lightgbm', 'catboost'. Doesn’t matter for survival analysis.
type	A string that determines if Machine Learning task is the 'binary_clf', 'regression', 'survival', or 'multiclass' task.

Value

A list of models for every engine.

ModelOriented/forester documentation built on June 6, 2024, 7:29 a.m.