static void InitValfri()
{
ValfriStatic.MatrixOfPoints = DictToMatrix.GetMatrix(Dataset.ListOfPoints);
ValfriStatic.Targets = GetTargetFromDataSet(ValfriStatic.MatrixOfPoints);
SetColor.Init(ValfriStatic.Targets);
ValfriStatic.MatrixOfPoints = RemoveIndexAndTarget(ValfriStatic.MatrixOfPoints);
Normalize.Initiate(ValfriStatic.MatrixOfPoints);
ValfriStatic.NormalizedMatrixOfPoints = Normalize.Matrix(ValfriStatic.MatrixOfPoints);
ValfriStatic.FeaturesToDisplay = Dataset.FeatureNames;
}
public static void NewPrediction()
{
if (usedFeatures.Count > 0)
{
NewDataPoints[0][usedFeatures[0]] = newPred[0];
NewDataPoints[0][usedFeatures[1]] = newPred[1];
NewDataPoints[0][usedFeatures[2]] = newPred[2];
}
else
{
NewDataPoints[0][NewDataPoints[0].Keys.ElementAt(1)] = newPred[0];
NewDataPoints[0][NewDataPoints[0].Keys.ElementAt(2)] = newPred[1];
NewDataPoints[0][NewDataPoints[0].Keys.ElementAt(3)] = newPred[2];
}
var obj = CreateNewObject(NewDataPoints[0].Keys.Count() - 2, NewDataPoints[0]);
var classified = Knn.Classify(obj, DictToMatrix.DictionaryListToMatrix(ListOfPoints), GetNumberOfTargets(GetDataSetTargets()), K);
if (classified is - 1)
{
return;
}
