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; }