Machine Learning

Functions for creating a model:

• F_VN_CreateBoostClassifier(Exp)
• F_VN_CreateKmppModel(Exp)
• F_VN_CreateKnnModel
• F_VN_CreateLbgModel(Exp)
• F_VN_CreateLdaTransform
• F_VN_CreateLdaTransformViaComponentNum
• F_VN_CreateNbcModel
• F_VN_CreatePcaTransform
• F_VN_CreatePcaTransformViaComponentNum
• F_VN_CreatePcaTransformViaVariance
• F_VN_CreateRTreesModel(Exp)
• F_VN_CreateStaModel(Exp)
• F_VN_CreateSvmModel(Exp)
• F_VN_CreateSvmSgdClassifier(Exp)

Functions for training a model:

• F_VN_TrainBatch
• F_VN_TrainBatchClusters
• F_VN_TrainSample
• F_VN_TrainSampleClass
• F_VN_TrainSampleCluster
• F_VN_TrainSampleScalar
• F_VN_TrainSampleVector

Functions for obtaining information on the cluster models:

• F_VN_GetClusterCenter
• F_VN_GetClusterNum

Functions for applying models to a sample:

• F_VN_GetSampleCluster(Exp)
• F_VN_GetSampleNovelty
• F_VN_PredictSampleClass (Exp)
• F_VN_PredictSampleScalar(Exp)
• F_VN_PredictSampleVector(Exp)

Functions for applying models to a batch:

• F_VN_GetBatchClusters(Exp)
• F_VN_GetBatchNovelties
• F_VN_PredictBatch(Exp)

Functions for applying models for feature transformation / dimension reduction:

• F_VN_FeatureTransform
• F_VN_InverseFeatureTransform

Functions for feature normalization:

• F_VN_GetFeatureScales
• F_VN_FeatureScaling(Exp)
• F_VN_InverseFeatureScaling(Exp)
• F_VN_InverseFeatureScaling(Exp)_REAL