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) { }