public DecisionTreeC4_5InfoViewModel(models.Task task, models.TaskSolver solver)
{
TaskName = task.Name;
Name = solver.Name;
TreeDescriptionC4_5 td = solver.Description as TreeDescriptionC4_5;
MaxTreeDepth = td.MaxDepth;
}
public void CreateSolver(string name, models.Task task)
{
int depth = MaxTreeDepth;
//WARNING!!!
//Here must be selected task template
//and number of inputs and outputs in it.
TreeDescriptionC4_5 td = new TreeDescriptionC4_5(Inputs, Outputs, depth);
TaskSolver ts = new TaskSolver()
{
Name = name,
TypeName = "DecisionTreeC4_5",
TaskID = task.ID,
Description = td
};
ts.save();
}
private void learnSolver()
{
foreach (LearningModel learningModel in LearningList)
{
TaskTemplate taskTemplate = (TaskTemplate)TaskTemplate.where (new Query("TaskTemplate").addTypeQuery(TypeQuery.select)
.addCondition("Name", "=", learningModel.SelectedPreprocessing), typeof(TaskTemplate))[0];
Selection selection = (Selection)Selection.where (new Query("Selection").addTypeQuery(TypeQuery.select)
.addCondition("TaskTemplateID", "=", taskTemplate.ID.ToString())
.addCondition("Name", "=", learningModel.SelectedSelection), typeof(Selection))[0];
int countRows = selection.RowCount;
LearningScenario learningScenario = (LearningScenario)LearningScenario.where (new Query("LearningScenario").addTypeQuery(TypeQuery.select)
.addCondition("Name", "=", learningModel.SelectedScenario), typeof(LearningScenario))[0];
List <Entity> selectionRows = SelectionRow.where (new Query("SelectionRow").addTypeQuery(TypeQuery.select)
.addCondition("SelectionID", "=", selection.ID.ToString()), typeof(SelectionRow));
List <Entity> parameters = dms.models.Parameter.where (new Query("Parameter").addTypeQuery(TypeQuery.select)
.addCondition("TaskTemplateID", "=", selection.TaskTemplateID.ToString()), typeof(dms.models.Parameter));
int stepRow = 0;
float[][] inputData = new float[countRows][];
float[] outputData = new float[countRows];
for (int i = 0; i < countRows; i++)
{
inputData[i] = new float[parameters.Count - 1];
}
int outputParam = 0;
for (int i = 0; i < parameters.Count; i++)
{
if (((models.Parameter)parameters[i]).IsOutput == 1)
{
outputParam = parameters[i].ID;
}
}
string[][] vals = Selection.valuesOfSelectionId(selection.ID);
float[][] fvals = new float[selection.RowCount][];
for (int i = 0; i < selection.RowCount; i++)
{
fvals[i] = new float[parameters.Count];
for (int j = 0; j < parameters.Count - 1; j++)
{
inputData[i][j] = float.Parse(vals[i][j].Replace(".", ","));
}
outputData[i] = float.Parse(vals[i][parameters.Count - 1].Replace(".", ","));
}
ISolver isolver = null;
if (Solver.Description is PerceptronTopology)
{
PerceptronTopology topology = Solver.Description as PerceptronTopology;
isolver = new PerceptronManaged(topology);
}
else if (Solver.Description is ConvNNTopology)
{
ConvNNTopology topology = Solver.Description as ConvNNTopology;
isolver = new ConvNNManaged(topology);
}
else if (Solver.Description is WardNNTopology)
{
WardNNTopology topology = Solver.Description as WardNNTopology;
isolver = new WardNNManaged(topology);
}
else if (Solver.Description is KohonenNNTopology)
{
KohonenNNTopology topology = Solver.Description as KohonenNNTopology;
isolver = new KohonenManaged(topology);
}
else if (Solver.Description is TreeDescription)
{
TreeDescription topology = Solver.Description as TreeDescription;
isolver = new DecisionTree(topology);
}
else if (Solver.Description is TreeDescriptionC4_5)
{
TreeDescriptionC4_5 topology = Solver.Description as TreeDescriptionC4_5;
isolver = new DecisionTreeC4_5(topology);
}
else
{
throw new EntryPointNotFoundException();
}
SeparationOfDataSet s = new SeparationOfDataSet(isolver, learningScenario, inputData, outputData);
LearnedSolver ls = new LearnedSolver()
{
SelectionID = selection.ID,
LearningScenarioID = learningScenario.ID,
TaskSolverID = Solver.ID,
Soul = s.separationAndLearn(selection.ID, outputParam)
};
ls.save();
LearningQuality lq = new LearningQuality()
{
LearnedSolverID = ls.ID,
MistakeTrain = Convert.ToInt32(s.MistakeTrain),
MistakeTest = Convert.ToInt32(s.MistakeTest),
ClosingError = s.ClosingError
};
lq.save();
}
OnClose?.Invoke(this, null);
}
public DecisionTree(TreeDescriptionC4_5 treeDesc) : base(treeDesc)
{
this.treeDesc = treeDesc;
}
