normalizePerformanceTable: Function to normalize (or rescale) the columns (or criteria)...

Description Usage Arguments Examples

View source: R/normalizePerformanceTable.R

Description

Standardizes the range of the criteria according to a few methods : percentage of max, scale between 0 and 1, scale to 0 mean and 1 standard deviation, scale to euclidian unit length.

Usage

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normalizePerformanceTable(performanceTable, 
                            normalizationTypes, 
                            alternativesIDs = NULL, 
                            criteriaIDs = NULL)

Arguments

performanceTable

A matrix containing the performance table to be plotted. The columns are labelled according to the criteria IDs, and the rows according to the alternatives IDs.

normalizationTypes

Vector indicating the type of normalization that should be applied to each of the criteria. Possible values : "percentageOfMax", "rescaling" (minimum becomes 0, maximum becomes 1), "standardization" (rescale to a mean of 0 and a standard deviation of 1), "scaleToUnitLength" (scale the criteria values such that the column has euclidian length 1). Any other value (like "none") will result in no data transformation. The elements are named according to the IDs of the criteria.

alternativesIDs

Vector containing IDs of alternatives, according to which the data should be filtered.

criteriaIDs

Vector containing IDs of criteria, according to which the data should be filtered.

Examples

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library(MCDA)

performanceTable <- matrix(runif(5*9), ncol=5)

row.names(performanceTable) <- c("x1","x2","x3","x4","x5","x6","x7","x8","x9")

colnames(performanceTable) <- c("g1","g2","g3","g4", "g5")

normalizationTypes <- c("percentageOfMax","rescaling",
                        "standardization","scaleToUnitLength", "none")

names(normalizationTypes) <- c("g1","g2","g3","g4","g5")

normalizedPerformanceTable <- normalizePerformanceTable(performanceTable,
                                                        normalizationTypes)

MCDA documentation built on Sept. 8, 2017, 5:07 p.m.