nbcTrain
Training the naive Bayes classifier (NBC)
Contents
Syntax
- [cPrm, logLike, recogRate, hitIndex]=nbcTrain(DS, opt, showPlot)
- DS: data set for training
- opt: parameters for training
- opt.prior: a vector of class prior probability
- (Data count based prior is assume if an empty matrix is given.)
- showPlot: 1 for plotting
- cPrm: cPrm.class(i) is the parameters for class i, etc.
- recogRate: recognition rate
- hitIndex: index of the correctly classified data points
Description
[cPrm, logLike, recogRate, hitIndex]=nbcTrain(DS, opt, showPlot) returns the training results of the naive bayes classifier
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]=nbcTrain(trainSet); [computedClass, logLike2, recogRate2, hitIndex]=nbcEval(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 = 96%
