public void Initialize()
{
IForecastingModel model = null;
Models = new List <IForecastingModel>();
AnnModelParameter annPara = new AnnModelParameter();
model = new NeuralNetworkModel(annPara);
Models.Add(model);
Heiflow.AI.SVM.Parameter p = new Heiflow.AI.SVM.Parameter();
model = new SVMModel(p);
Models.Add(model);
ModelParameter mp = new ModelParameter();
model = new MLRModel(mp);
Models.Add(model);
Recognizers = new List <IRecognizer>();
foreach (var mm in Models)
{
var recognizer = new ImageRecognizer(mm, _IImageSetsBuilder, _IColorClassification);
Recognizers.Add(recognizer);
}
}
public static IForecastingModel CreateForecastingModel(string name)
{
IForecastingModel model = null;
switch (name)
{
case "Artificial Neural Network":
AnnModelParameter annPara = new AnnModelParameter();
model = new NeuralNetworkModel(annPara);
break;
case "HIGANN":
AnnModelParameter annPara1 = new AnnModelParameter();
model = new NeuralNetworkModel(annPara1);
break;
case "Support Vector Machine":
Heiflow.AI.SVM.Parameter p = new Heiflow.AI.SVM.Parameter();
model = new SVMModel(p);
break;
case "Multiple Linear Regression":
ModelParameter mp = new ModelParameter();
model = new MLRModel(mp);
break;
case "Genetic Programming":
GPModelParameter para = new GPModelParameter();
model = new GPModel(para);
break;
case "Model Tree":
Rule root = new Rule(5, 0.47035, RuleType.Interior);
Rule right = new Rule(RuleType.RightLeaf);
root.RightChild = right;
Rule left = new Rule(5, 0.30445, RuleType.Interior);
root.LeftChild = left;
Rule left1 = new Rule(RuleType.LeftLeaf);
left.LeftChild = left1;
Rule right1 = new Rule(9, 0.156, RuleType.Interior);
left.RightChild = right1;
Rule right1_left = new Rule(RuleType.LeftLeaf);
right1.LeftChild = right1_left;
Rule right1_right = new Rule(RuleType.RightLeaf);
right1.RightChild = right1_right;
HybridModelParameter hmp = new HybridModelParameter(root);
model = new HybridModel(hmp);
break;
}
return(model);
}
