private IClassifierML get_cls(Func <double[], double[]>[] functions, Task task)
{
LabeledData[] ldata = collect_samples(functions, task);
IClassifierML cls = new RandomForest();
RandomForestParams ps = new RandomForestParams(ldata, ldata.Length /* samples count */,
featureCount /* features count */,
2 /* classes count */,
100 /* trees count */,
1 /* count of features to do split in a tree */,
0.7 /* percent of a training set of samples */
/* used to build individual trees. */);
cls.train <int>(ps);
return(cls);
}
private IClassifierML get_rg(Func <double[], double[]>[] functions, Task task)
{
LabeledData[] ldata = collect_samples(functions, task);
IClassifierML ml = new RandomForest();
RandomForestParams ps = new RandomForestParams(ldata.ToArray(),
ldata.Length /* samples count */,
featureCount /* features count */,
1 /* classes count */,
TreesCount /* trees count */,
3 /* count of features to do split in a tree */,
0.7 /* percent of a training set of samples */
/* used to build individual trees. */);
ml.train <double>(ps);
double trainModelPrecision;
ml.validate <double>(ldata.ToArray(), out trainModelPrecision);
Console.WriteLine("Model precision on training dataset: " + trainModelPrecision);
return(ml);
}
