model_weighting: Model weighting

In vcerqueira/tsensembler: Dynamic Ensembles for Time Series Forecasting

Description

This is an utility function that takes the raw error of models and scales them into a 0-1 range according to one of three strategies:

Usage

model_weighting(x, trans = "softmax", ...)

Arguments

x	A object describing the loss of each base model
trans	Character value describing the transformation type. The available options are softmax, linear and erfc. The softmax and erfc provide a non-linear transformation where the weights decay exponentially as the relative loss of a given model increases (with respect to all available models). The linear transformation is a simple normalization of values using the max-min method.
...	Further arguments to normalize and proportion functions \(na.rm = TRUE\)

Details

erfc

using the complementary Gaussian error function

softmax

using a softmax function

linear

A simple normalization using max-min method

These tranformations culminate into the final weights of the models.

Value

An object describing the weights of models

See Also

Other weighting base models: EMASE, build_committee, get_top_models, model_recent_performance, select_best

vcerqueira/tsensembler documentation built on Oct. 28, 2020, 11:46 p.m.