//for multi-task
public toolbox(dataSet X, List <dataSet> XList, bool train = true)
{
if (train)//to train
{
_X = X;
_XList = XList;
_fGene = new featureGenerator(X);
_model = null;
_modelList = new List <model>();
for (int i = 0; i < Global.nTask; i++)
{
model m = new model(XList[i], _fGene);
_modelList.Add(m);
}
_inf = new inference(this);
_grad = new gradient(this);
initOptimizer();
}
else//to test
{
_X = X;
_XList = XList;
_model = null;
_modelList = new List <model>();
for (int i = 0; i < Global.nTask; i++)
{
model m = new model(Global.modelDir + i.ToString() + Global.fModel);
_modelList.Add(m);
}
_fGene = new featureGenerator(X);
_inf = new inference(this);
_grad = new gradient(this);
}
}
public toolbox(dataSet X, bool train = true)
{
if (train)//to train
{
_X = X;
_fGene = new featureGenerator(X);
_model = new model(X, _fGene);
_inf = new inference(this);
_grad = new gradient(this);
initOptimizer();
}
else//to test
{
_X = X;
_model = new model(Global.fModel);
_fGene = new featureGenerator(X);
_inf = new inference(this);
_grad = new gradient(this);
}
}
public inference(toolbox tb)
{
_optim = tb.Optim;
_fGene = tb.FGene;
_grad = tb.Grad;
}
