fforms_ensemble

a matrix of votes of probabilities based of fforms random forest classifier

votematrix

threshold value for sum of probabilities of votes, default is 0.5

threshold

This function identify models to be use in producing combination forecast

A novel meta-learning framework for forecast model selection using time series features. Many applications require a large number of time series to be forecast. Providing better forecasts for these time series is important in decision and policy making. We propose a classification framework which selects forecast models based on features calculated from the time series. We call this framework FFORMS (Feature-based FORecast Model Selection). FFORMS builds a mapping that relates the features of time series to the best forecast model using a random forest. 'seer' package is the implementation of the FFORMS algorithm. For more details see our paper at <https://www.monash.edu/business/econometrics-and-business-statistics/research/publications/ebs/wp06-2018.pdf>.

Thiyanga Talagala

fforms_ensemble: Function to identify models to compute combination forecast using FFORMS algorithm

Description

Usage

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