predict_fc_model: Predicts the forecasting method for the inputed time series.

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

Description

This is a function to predict the forecasting method based on the the inputed training method fitted_model for the new data new_data. Only the following caret models are supported: 'nnet', 'xgbLinear', 'xgbTree', 'svmLinear', 'svmPoly', 'ann', 'catboost', 'C5.0'. As input is only required an time series object and a fitted classification model of class 'train'.

Usage

predict_fc_model(fitted_model, time_series, ts_taxonomy = "v1")

Arguments

fitted_model	A machine learning classification training model
time_series	Either a vector, time series or data.frame object representing a time series is allowed.
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 predicted class for the inputed new time series time_series.

Examples

predict_fc_model()

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