train_c50_rule_model: Generates a rule based trainings model.

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

Description

This is a function to generate a C5.0 rule model for the 1000 time series from the tstaxonomyr R package. The best fitted model is identified based number of boosting trials boosting_length. The method 'C5.0' from the 'C50' R package is fitted and afterwards returned. As input is only required the boosting_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_c50_rule_model(boosting_length = 10, ts_taxonomy = "v1")

Arguments

boosting_length	Number of model boosting 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 trained rule model from the C5.0 algorithm.

Examples

fitted_model <- train_c50_rule_model()

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