/
cartree.sg
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/
cartree.sg
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CSVFile f_feats_train("../../data/classifier_4class_2d_linear_features_train.dat")
CSVFile f_feats_test("../../data/classifier_4class_2d_linear_features_test.dat")
CSVFile f_labels_train("../../data/classifier_4class_2d_linear_labels_train.dat")
CSVFile f_labels_test("../../data/classifier_4class_2d_linear_labels_test.dat")
Math:init_random(1)
#![create_features]
RealFeatures features_train(f_feats_train)
RealFeatures features_test(f_feats_test)
MulticlassLabels labels_train(f_labels_train)
MulticlassLabels labels_test(f_labels_test)
#![create_features]
#![set_attribute_types]
BoolVector ft(2)
ft[0] = False
ft[1] = False
#![set_attribute_types]
#![create_instance]
CARTree classifier(ft,enum EProblemType.PT_MULTICLASS, 5, True)
classifier.set_labels(labels_train)
#![create_instance]
#![train_and_apply]
classifier.train(features_train)
MulticlassLabels labels_predict = classifier.apply_multiclass(features_test)
#![train_and_apply]
#![evaluate_accuracy]
MulticlassAccuracy eval()
real accuracy = eval.evaluate(labels_predict, labels_test)
#![evaluate_accuracy]
# integration testing variables
RealVector output = labels_predict.get_labels()