public void Statistics_Mode_Single_Value()
{
double[] na = new double[] { 1 };
double value = Dispersion.Mode(na);
Assert.AreEqual(1, value);
}
double RunModelForSingleData(double[] data)
{
VerifyDataForRun(data);
double[] values =
new double[_allTrees.Length];
int idx = 0;
//Iterate through all trees
foreach (ModelCART modelCart in _allTrees)
{
values[idx++] =
modelCart.RunModelForSingleData(data);
}
double finalValue = Dispersion.Mode(values);
return(finalValue);
}
public override double RunModelForSingleData(double[] data)
{
double value = 0;
VerifyDataForRun(data);
if (data.Length != _data.Length - 1)
{
throw new InvalidDataException();
}
KeyValuePair <int, double>[] allValues =
new KeyValuePair <int, double> [_data[0].Length];
//Compute distance per Row
Parallel.For(0, _data[0].Length, new ParallelOptions {
MaxDegreeOfParallelism = _maxParallelThreads
}, row =>
{
double[] tArray = SupportFunctions.GetLinearArray(_data, row, _data.Length - 2);
double distance = _distanceMeasure.getDistanceVector(tArray, data);
allValues[row] = new KeyValuePair <int, double>(row, distance);
});
List <KeyValuePair <int, double> > distList =
SupportFunctions.GetSortedKeyValuePair(allValues);
double[] targetValues = new double[_k];
//Get lowest k distancesPerRow and their count
//for (int ii= 0; ii < _k;ii++)
Parallel.For(0, _k, new ParallelOptions {
MaxDegreeOfParallelism = _maxParallelThreads
}, ii =>
{
int row = distList[ii].Key;
targetValues[ii] = _data[_origTargetAttributeIndex][row];
});
//Get the mode
value = Dispersion.Mode(targetValues);
return(value);
}
public void Statistics_Mode()
{
double value = Dispersion.Mode(ta);
Assert.AreEqual(Double.NaN, value);
}
