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
