def multiclass_cartree_modular(train=traindat,test=testdat,labels=label_traindat,ft=feattypes): try: from modshogun import RealFeatures, MulticlassLabels, CSVFile, CARTree, PT_MULTICLASS except ImportError: print("Could not import Shogun modules") return # wrap features and labels into Shogun objects feats_train=RealFeatures(CSVFile(train)) feats_test=RealFeatures(CSVFile(test)) train_labels=MulticlassLabels(CSVFile(labels)) # CART Tree formation with 5 fold cross-validation pruning c=CARTree(ft,PT_MULTICLASS,5,True) c.set_labels(train_labels) c.train(feats_train) # Classify test data output=c.apply_multiclass(feats_test).get_labels() return c,output
def multiclass_cartree_modular(train=traindat, test=testdat, labels=label_traindat, ft=feattypes): try: from modshogun import RealFeatures, MulticlassLabels, CSVFile, CARTree, PT_MULTICLASS except ImportError: print("Could not import Shogun modules") return # wrap features and labels into Shogun objects feats_train = RealFeatures(CSVFile(train)) feats_test = RealFeatures(CSVFile(test)) train_labels = MulticlassLabels(CSVFile(labels)) # CART Tree formation with 5 fold cross-validation pruning c = CARTree(ft, PT_MULTICLASS, 5, True) c.set_labels(train_labels) c.train(feats_train) # Classify test data output = c.apply_multiclass(feats_test).get_labels() return c, output