tiger (version 0.2.3.1)

correlated: Calculate correlation structure

Description

Calculate the correlation structure between multiple performance measures

Usage

correlated(result, limit = 0.85, plot.scatter = FALSE, keep = NA)
correl(measures, limit = 0.85, plot.scatter = FALSE, keep = NA)

Arguments

result

object returned from tiger

measures

data.frame for which to determine correlation structure

limit

Limit for absolute correlation, above which data is considered to be correlated

plot.scatter

Boolean, indicating whether to show pairwise plots for correlated measures

keep

Vector with names of measures that must not be excluded because of correlation with other measures

Value

correl returns:

pairs

Matrix with indices of pairwise correlated measures

pairs.by.name

Matrix with measure names of pairwise correlated measures

possible.exclusion

List indicating which measures might be removed to end up with no strongly correlated measures. The list also indicates, which measure is correlated to the removed measures

to.drop

List of indices for measures to drop (according to previous list)

to.drop.by.name

List of measure names (of the previous list)

correlated returns a list of two correl results, one for the original performance measures and one for the transformed measures from a result from tiger.

See Also

This method helps to reduce the amount of data to be analyzed from an evaluation using tiger

Examples

data(tiger.example)
correlated <- correlated(tiger.single, keep=c("CE","RMSE" ))