getDataRotNorm2: Generates data of rotating normal (two-dimensional)...

In aschersleben/NBCD: Naive Bayes for Online Classification with Concept Drift

Description

Generates data of rotating normal (two-dimensional) distributions.

Usage

getDataRotNorm2(angle, n.obs = 1, sd = sqrt(0.2), both = FALSE, time)

Arguments

angle	[numeric(1)] Rotation angle of the means in relation to the y axis (clockwise).
n.obs	[numeric(1)] Number of observations to draw from the "concept" (distribution).
sd	[numeric(1)] Standard deviation of the normal distributions.
both	[logical(1)] If TRUE, observations are equally distributed to both classes. Default is FALSE.
time	[numeric] The time stamp to attach to the data. If missing, it's the "angle" argument.

Value

[list]

Examples

set.seed(1909)
dat <- getDataRotNorm2(45, 100)
plot(dat$x, col = dat$class)

aschersleben/NBCD documentation built on May 12, 2019, 4:32 a.m.