public void do_random_forest_analyse(Classifiers.IClassifier cls, double allowErr, Func <double[], double> meFunc, Func <double[], double[]> calcDerivative)
{
int[] count = new int[N]; for (int i = 0; i < N; i++)
{
count[i] = (Min[i] == Max[i]) ? 1 : NGRID;
}
create_grid(count);
analyse_voronoi();
analyse_error();
int n = candidates.Length;
Console.WriteLine(candidates.Length);
//int n = grid.Node.Length;
Classifiers.LabeledData[] ldata = new Classifiers.LabeledData[n];
int featureCount = 0;
for (int i = 0; i < n; i++)
{
// min, max in locality
double maxNeighbours = double.MinValue;
double minNeighbours = double.MaxValue;
foreach (var neighbour in grid.Neighbours(candidates[i]))
//foreach (var neighbour in grid.Neighbours(i))
{
double[] calcNeighbour = (double[])grid.Node[neighbour].Clone();
this.func.Calculate(calcNeighbour);
if (calcNeighbour[calcNeighbour.Length - 1] < minNeighbours)
{
minNeighbours = calcNeighbour[calcNeighbour.Length - 1];
}
if (calcNeighbour[calcNeighbour.Length - 1] > maxNeighbours)
{
maxNeighbours = calcNeighbour[calcNeighbour.Length - 1];
}
}
// current val
double[] cuurentNode = (double[])grid.Node[candidates[i]].Clone();
// double[] cuurentNode = (double[])grid.Node[i].Clone();
this.func.Calculate(cuurentNode);
double cuurentNodeVal = cuurentNode[cuurentNode.Length - 1];
if (cuurentNodeVal < minNeighbours)
{
minNeighbours = cuurentNodeVal;
}
if (cuurentNodeVal > maxNeighbours)
{
maxNeighbours = cuurentNodeVal;
}
// is real function and approximation are equal, class for point
//derivative
double[] derivative = calcDerivative(grid.Node[candidates[i]]);
//double[] derivative = calcDerivative(grid.Node[i]);
// build features vector
double[] features = new double[5 + derivative.Length];
features[0] = borderdist[i];
features[1] = error[i];
features[2] = maxNeighbours;
features[3] = minNeighbours;
features[4] = cuurentNodeVal;
for (int k = 0; k < derivative.Length; k++)
{
features[5 + k] = derivative[k];
}
ldata[i] = new Classifiers.LabeledData(features, 0);
featureCount = features.Length;
}
List <int> newCandidates = new List <int>();
int[] y = new int[ldata.Length];
for (int i = 0; i < ldata.Length; i++)
{
cls.infer(ldata[i].data, out y[i]);
if (y[i] == 1)
{
//newCandidates.Add(candidates[i]);
newCandidates.Add(i);
}
}
candidates = newCandidates.ToArray();
Console.WriteLine(candidates.Length);
xfcandidates = Tools.Sub(grid.Node, candidates);
}
