private MultinomialLogitModel(MultinomialLogitModel original, Cloner cloner)
: base(original, cloner) {
logitModel = new alglib.logitmodel();
logitModel.innerobj.w = (double[])original.logitModel.innerobj.w.Clone();
allowedInputVariables = (string[])original.allowedInputVariables.Clone();
classValues = (double[])original.classValues.Clone();
}
private MultinomialLogitModel(MultinomialLogitModel original, Cloner cloner)
: base(original, cloner)
{
logitModel = new alglib.logitmodel();
logitModel.innerobj.w = (double[])original.logitModel.innerobj.w.Clone();
allowedInputVariables = (string[])original.allowedInputVariables.Clone();
classValues = (double[])original.classValues.Clone();
}
private MultinomialLogitModel(MultinomialLogitModel original, Cloner cloner)
: base(original, cloner)
{
logitModel = new alglib.logitmodel();
logitModel.innerobj.w = (double[])original.logitModel.innerobj.w.Clone();
allowedInputVariables = (string[])original.allowedInputVariables.Clone();
classValues = (double[])original.classValues.Clone();
this.factorVariables = original.factorVariables.Select(kvp => new KeyValuePair <string, IEnumerable <string> >(kvp.Key, new List <string>(kvp.Value))).ToList();
}
public MultinomialLogitClassificationSolution(MultinomialLogitModel logitModel, IClassificationProblemData problemData)
: base(logitModel, problemData)
{
}
public MultinomialLogitClassificationSolution( MultinomialLogitModel logitModel,IClassificationProblemData problemData)
: base(logitModel, problemData) {
}