public Dictionary <string, List <object> > ModelEvaluation()
{
var bs = Factory.ProgresReport.BestSolution;
var par = Factory.Parameters;
var dic = new Dictionary <string, List <object> >();
//
if (bs != null)
{
//get output for training data set
var yy = ExpData.GetColumnOutputValues(false);
var y1 = yy[0];//Inputs.GetDataOutputCol(true);//experiment
var output = calculateOutput(true, true);
//get output for testing data set if available
var yy1 = ExpData.GetColumnOutputValues(true);
var y2 = yy1 != null ? yy1[0] : null;//Inputs.GetDataOutputCol(false);//experiment
var outputt = calculateOutput(false, true);
//
var col = ExpData.GetColumnsFromOutput().FirstOrDefault();
if (col.ColumnDataType == ColumnType.Binary || col.ColumnDataType == ColumnType.Category)
{
dic.Add("Classes", col.Statistics.Categories.ToList <object>());
}
//add data sets
dic.Add("obs_train", y1.Select(x => (object)x).ToList <object>());
dic.Add("prd_train", output.Select(x => (object)x).ToList <object>());
//add test dataset
if (y2 != null)
{
dic.Add("obs_test", y2.Select(x => (object)x).ToList <object>());
dic.Add("prd_test", outputt.Select(x => (object)x).ToList <object>());
}
return(dic);
}
return(null);
}
public bool setLearningType(Parameters param)
{
//determine the type of ML
param.OutputType = ExpData.GetOutputColumnType();
if (param.OutputType == ColumnType.Binary)
{
if (param.RootName.StartsWith("Sigm"))
{
param.RootFunctionNode = new Function()
{
Id = 2048, Name = "Sigmoid", Arity = 1, HasParameter = true, Parameter = param.Threshold, Parameter2 = 2
}
}
;
else if (param.RootName.StartsWith("Step"))
{
param.RootFunctionNode = new Function()
{
Id = 2049, Name = "Step", Arity = 1, HasParameter = true, Parameter = param.Threshold, Parameter2 = 2
}
}
;
else if (param.RootName.StartsWith("Scal"))
{
param.RootFunctionNode = new Function()
{
Id = 2050, Name = "SSigmoid", Arity = 1, HasParameter = true, Parameter = param.Threshold, Parameter2 = 2
}
}
;
else if (param.RootName.StartsWith("Soft"))
{
param.RootFunctionNode = new Function()
{
Id = 2051, Name = "Softmax", Arity = 2, Parameter2 = 2
}
}
;
}
else if (param.OutputType == ColumnType.Category)
{
var clss = ExpData.GetColumnsFromOutput().FirstOrDefault().Statistics.Categories.Count;
if (param.RootName.StartsWith("Scal"))
{
param.RootFunctionNode = new Function()
{
Id = 2050, Name = "SSigmoid", Arity = 1, HasParameter = true, Parameter = clss, Parameter2 = clss
}
}
;
else if (param.RootName.StartsWith("Soft"))
{
param.RootFunctionNode = new Function()
{
Id = 2051, Name = "Softmax", Arity = clss, Parameter2 = clss
}
}
;
else
{
throw new Exception("Predefined Root Node is not compatible with multi class classification modeling!");
}
}
else if (param.OutputType == ColumnType.Numeric)
{
if (param.RootName.StartsWith("Pol3"))
{
param.RootFunctionNode = Globals.GetFunction(2039);// new Function() { Id = 2050, Name = "P3", Arity = 1, HasParameter = true, Parameter = clss, Parameter2 = clss };
}
}
return(true);
}