train_catboost: Generates a classification catboost trainings model.

In mowomoyela/tsfcmethodr: Classification methods to predict best performing forecasting method of a ts

Description

This is a function to generate a catboost classification model for the 1000 time series from the tstaxonomyr R package. The best fitted ann model is identified based on the k-fold cv_nfold cross-validation and the number of rounds n_round. The method 'catboost' from 'caret' package is fitted and afterwards returned. As input is only required the n_round, cv_nfold and tune_length with a number between 1 and 100. Also, for ts_taxonomy only 'v1' for the basic taxonomy or 'v2' for the ligther feature selected taxonomy of the tstaxonomyr R package are allowed. Otherwise the function returns an error message.

Usage

train_catboost(n_round = 10, cv_nfold = 10, tune_length = 10,
  ts_taxonomy = "v1")

Arguments

n_round	Number of cross-validation rounds.
cv_nfold	Number of folds of cross-validation.
tune_length	Number of model tuning intervals.
ts_taxonomy	Either 'v1' or 'v2'. v1 uses the default time series taxonomy and v2 the feature selected ts taxonomy of the tstaxonomyr package.

Value

The best fitted catboost classification model.

Examples

fitted_model <- train_catboost()

mowomoyela/tsfcmethodr documentation built on May 15, 2019, 4:47 p.m.