public EnsembleLearningPredictionEngine(MLNetClassifier clf, bool UsePCA = false)
{
if (!UsePCA)
{
InitiateClassifier(clf);
}
else
{
InitiateClassifierWithPCA(clf);
}
}
public MLNetSignPrediction(MLNetClassifier clf, bool UsePCA = false)
{
if (!UsePCA)
{
InitiateClassifier(clf);
}
else
{
InitiateClassifierWithPCA(clf);
}
}
public MLNetHierarchicalSignPrediciton(MLNetClassifier clf, bool UsePCA = false)
{
if (!UsePCA)
{
InitiateClassifier(clf);
}
else
{
InitiateClassifierWithPCA(clf);
}
}
public void InitiateClassifierWithPCA(MLNetClassifier clf)
{
if (clf == MLNetClassifier.LightGBM)
{
mLContext = new MLContext(seed: 0);
trainedModel = mLContext.Model.Load(Environment.CurrentDirectory + "\\Models\\model_LightGBM Single Model pca 100.zip", out schema);
prediction = mLContext.Model.CreatePredictionEngine <InputData, OutPutData>(trainedModel);
}
else if (clf == MLNetClassifier.L_BFGS)
{
mLContext = new MLContext(seed: 0);
trainedModel = mLContext.Model.Load(Environment.CurrentDirectory + "\\Models\\model_L-BFGS Single Model PCA 100.zip", out schema);
prediction = mLContext.Model.CreatePredictionEngine <InputData, OutPutData>(trainedModel);
}
}
public void InitiateClassifier(MLNetClassifier clf)
{
if (clf == MLNetClassifier.L_BFGS)
{
signClassification = LoadModel("model_LBFGS SignClassification Model.zip");
numberPrediciton = LoadModel("model_LBFGS Number Model.zip");
alphabetPredicion = LoadModel("model_LBFGS Alphabet Model.zip");
commonSignPrediciton = LoadModel("model_LBFGS CommonSign Model.zip");
}
else if (clf == MLNetClassifier.LightGBM)
{
signClassification = LoadModel("model_LightGBM SignCategorical Model.zip");
numberPrediciton = LoadModel("model_LightGBM Number Model.zip");
alphabetPredicion = LoadModel("model_LightGBM Alphabet Model.zip");
commonSignPrediciton = LoadModel("model_LightGBM CommonSign Model.zip");
}
}
public void InitiateClassifier(MLNetClassifier clf)
{
mLContext = new MLContext();
if (clf == MLNetClassifier.LightGBM)
{
var filenames = Directory.GetFiles(Environment.CurrentDirectory + $"\\Models\\Bagging\\Light GBM");
foreach (var file in filenames)
{
var trainedModel = mLContext.Model.Load(file, out schema);
prediction.Add(mLContext.Model.CreatePredictionEngine <InputData, OutPutData>(trainedModel));
}
}
else if (clf == MLNetClassifier.L_BFGS)
{
var filenames = Directory.GetFiles(Environment.CurrentDirectory + $"\\Models\\Bagging\\LBFGS");
foreach (var file in filenames)
{
var trainedModel = mLContext.Model.Load(file, out schema);
prediction.Add(mLContext.Model.CreatePredictionEngine <InputData, OutPutData>(trainedModel));
}
}
}
public void InitiateClassifierWithPCA(MLNetClassifier clf)
{
//throw new NotImplementedException();
}
public void InitiateClassifierWithPCA(MLNetClassifier clf)
{
}
