correlated {tiger}R Documentation

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.

Author(s)

Dominik Reusser

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" ))

[Package tiger version 0.2 Index]