lol.sims.xor2: Xor Problem

In lolR: Linear Optimal Low-Rank Projection

Description

A function to simulate from the 2-class xor problem.

Usage

lol.sims.xor2(n, d, priors = NULL, fall = 100)

Arguments

n	the number of samples of the simulated data.
d	the dimensionality of the simulated data.
priors	the priors for each class. If NULL, class priors are all equal. If not null, should be |priors| = K, a length K vector for K classes. Defaults to NULL.
fall	the falloff for the covariance structuring. Sigma declines by ndim/fall across the variance terms. Defaults to 100.

Value

A list of class simulation with the following:

X	[n, d] the n data points in d dimensions as a matrix.
Y	[n] the n labels as an array.
mus	[d, K] the K class means in d dimensions.
Sigmas	[d, d, K] the K class covariance matrices in d dimensions.
priors	[K] the priors for each of the K classes.
simtype	The name of the simulation.
params	Any extraneous parameters the simulation was created with.

Details

For more details see the help vignette: vignette("sims", package = "lolR")

Author(s)

Eric Bridgeford

Examples

library(lolR)
data <- lol.sims.xor2(n=200, d=30)  # 200 examples of 30 dimensions
X <- data$X; Y <- data$Y

lolR documentation built on July 8, 2020, 7:35 p.m.