public void NaiveBayes_gaussian_jason_all_training_samples()
{
initData_dataset_gaussian_naive_bayes_jason_example();
BuildGaussianNaiveBayes bnb = new BuildGaussianNaiveBayes();
ModelBase model = (ModelBase)bnb.BuildModel
(_trainingData, _attributeHeaders, _indexTargetAttribute);
double[] data;
double value;
int count = 0;
data = new double[_trainingData.Length - 1];
for (int row = 0; row < _trainingData[0].Length; row++)
{
for (int col = 0; col < _trainingData.Length - 1; col++)
{
data[col] =
_trainingData[col][row];
}
value = model.RunModelForSingleData(data);
if (value == _trainingData[_indexTargetAttribute][row])
{
count++;
}
}
Assert.AreEqual(count, 10);
}
public void NaiveBayes_gaussian_jason_single_training_sample_positive()
{
initData_dataset_gaussian_naive_bayes_jason_example();
BuildGaussianNaiveBayes bnb = new BuildGaussianNaiveBayes();
ModelBase model = (ModelBase)bnb.BuildModel
(_trainingData, _attributeHeaders, _indexTargetAttribute);
double[] data;
double value;
data = GetSingleTrainingRowDataForTest(0);
value = model.RunModelForSingleData(data);
Assert.AreEqual(value,
_trainingData[_indexTargetAttribute][0]);
}