Learn R Programming

mlr (version 2.4)

measures: Performance measures.

Description

A performance measure is evaluated after a single train/predict step and returns a single number to assess the quality of the prediction (or maybe only the model, think AIC). The measure itself knows whether it wants to be minimized or maximized and for what tasks it is applicable.

All supported measures can be found by listMeasures or as a table in the tutorial appendix: http://berndbischl.github.io/mlr/tutorial/html/measures/.

If you want a measure for a misclassification cost matrix, look at makeCostMeasure. If you want to implement your own measure, look at makeMeasure.

Most measures can directly be accessed via the function named after the scheme measureX (e.g. measureSSE).

For clustering measures, we compact the predicted cluster IDs such that they form a continuous series starting with 1. If this is not the case, some of the measures will generate warnings.

Usage

featperc

timetrain

timepredict

timeboth

sse

measureSSE(truth, response)

mse

measureMSE(truth, response)

rmse

measureRMSE(truth, response)

medse

measureMEDSE(truth, response)

sae

measureSAE(truth, response)

mae

measureMAE(truth, response)

medae

measureMEDAE(truth, response)

mmce

measureMMCE(truth, response)

acc

measureACC(truth, response)

ber

multiclass.auc

auc

measureAUC(probabilites, truth, negative, positive)

brier

measureBrier(probabilites, truth, negative, positive)

bac

measureBAC(truth, response, negative, positive)

tp

measureTP(truth, response, positive)

tn

measureTN(truth, response, negative)

fp

measureFP(truth, response, positive)

fn

measureFN(truth, response, negative)

tpr

measureTPR(truth, response, positive)

tnr

measureTNR(truth, response, negative)

fpr

measureFPR(truth, response, negative, positive)

fnr

measureFNR(truth, response, negative, positive)

ppv

measurePPV(truth, response, positive)

npv

measureNPV(truth, response, negative)

fdr

measureFDR(truth, response, positive)

mcc

measureMCC(truth, response, negative, positive)

f1

gmean

measureGMEAN(truth, response, negative, positive)

gpr

measureGPR(truth, response, positive)

cindex

meancosts

mcp

db

dunn

G1

G2

silhouette

Arguments

docType

data

format

none

See Also

Other performance: Measure, makeMeasure; makeCostMeasure; makeCustomResampledMeasure; performance