public bool CalculatePrediction(DataSetValue testExample)
{
var probabilityOfZeroAndOne = NaiveBayesCalculator.ObtainProbabilityOfZeroAndOne(testExample.Values,
naiveBayesTrainingDataStructure, probabilityOfOne);
bool isOnePrediction = (probabilityOfZeroAndOne.Item2) > probabilityOfZeroAndOne.Item1 * 4.5;
return(isOnePrediction);
}
public static bool CalculatePrediction(List <DecisionTreeLevel> decisionTrees, DataSetValue inputValues)
{
int positiveCount = 0, negativeCount = 0;
foreach (var decisionTree in decisionTrees)
{
bool localOutput = decisionTree.Evaluate(inputValues.Values);
if (localOutput)
{
positiveCount++;
}
else
{
negativeCount++;
}
}
bool output = positiveCount > negativeCount;
return(output);
}
