model_weighting {tsensembler}

Model weighting

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()