mutUniformResetSHW: Uniform Reset Scaled by Hamming Weight
In mosmafs: Multi-Objective Simultaneous Model and Feature Selection

mutUniformResetSHW

R Documentation

Uniform Reset Scaled by Hamming Weight

Description

Combination of the idea of mutBitflipCHW with mutUniformReset.

If a given bitvector has m 1s and n 0s, then, with probability p for each bit, it is drawn anew from the distribution ((m + 1) * reset.dist) / (m * reset.dist + n * (1 - reset.dist) + 1).

The reasoning behind this is that, without Laplace smoothing, drawing from m * reset.dist / (m * reset.dist + n * (1 - reset.dist))would lead to probabilities of drawing a "0" or "1" such thatmean(P("1") / P("0")) = m / n * mean(reset.dist / (1 - reset.dist))'.

The mutUniformMetaResetSHW does reset with a weighted mean of distributions.

Usage

mutUniformResetSHW(ind, p = 0.1, reset.dist, ...)

mutUniformMetaResetSHW(ind, p = 0.1, reset.dists, reset.dist.weights, ...)

Arguments

`ind`	`[integer]` binary individual.
`p`	`[numeric]` average reset probability, must be between 0 and 1.
`reset.dist`	`[numeric]` approximate probability to draw 1-bit per entry.
`...`	further arguments passed on to the method.
`reset.dists`	`[matrix]` columns of probabilities, with `length(ind)` cols and `length(reset.dist.weights)` rows.
`reset.dist.weights`	`[numeric]` weight vector to select among `reset.dist` columns.