Exemple #1
0
        private void TrainingStats(EvalParameters evalParams)
        {
            var numCorrect = 0;

            for (var ei = 0; ei < numUniqueEvents; ei++)
            {
                for (var ni = 0; ni < numTimesEventsSeen[ei]; ni++)
                {
                    var modelDistribution = new double[numOutcomes];

                    NaiveBayesModel.Eval(contexts[ei], values?[ei], modelDistribution, evalParams);

                    var max = MaxIndex(modelDistribution);
                    if (max == outcomeList[ei])
                    {
                        numCorrect++;
                    }
                }
            }
            var trainingAccuracy = (double)numCorrect / numEvents;

            Display("Stats: (" + numCorrect + "/" + numEvents + ") " + trainingAccuracy);
        }