qcEval

Evaluation for the QC (quadratic classifier)

Contents

Syntax

Description

[computedClass, logLike, recogRate, hitIndex]=qcEval(DS, cPrm) returns the evaluation results of QC

• DS: dataset
• cPrm: QC parameters
• computedClass: computed class of each data instance
• logLike: log likelihood of each data instance
• recogRate: recognition rate of the QC
• hitIndex: vector of the hit indices of the dataset

If DS does not have "output" field, then this command won't return "recogRate" and "hitIndex".

Example

DS=prData('iris');
DS.input=DS.input(3:4, :);
trainSet.input=DS.input(:, 1:2:end); trainSet.output=DS.output(:, 1:2:end);
testSet.input=DS.input(:, 2:2:end);  testSet.output=DS.output(:, 2:2:end);
[cPrm, logLike1, recogRate1]=qcTrain(trainSet);
[computedClass, logLike2, recogRate2, hitIndex]=qcEval(testSet, cPrm, 1);
fprintf('Inside recog rate = %g%%\n', recogRate1*100);
fprintf('Outside recog rate = %g%%\n', recogRate2*100);

Inside recog rate = 97.3333%
Outside recog rate = 97.3333%

See Also

qcTrain.

Published with MATLAB® R2018a