What is relaxed tree in shogun? Explain with an example.

This recipe explains what is relaxed tree in shogun with an example.

Recipe Objective

This recipe explains what is relaxed tree explain with an example.
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Relaxed Tree

The relaxed tree algorithm is also known as the relaxed hierarchy algorithm. It is used to compute multi-class classification problems by damaging the relaxed hierarchy structure of the data.
At every node, a binary classifier split the data into three groups. 1 and -1 are the positive and negative sample groups while classes, labeled with 0, are ignored by the binary classifier. The child of each node contains either group 0 and 1, or group 0 and -1.

x_train = RealFeatures(feats_train)
x_test = RealFeatures(feats_test)
y_train = MulticlassLabels(labels_train)
y_test = MulticlassLabels(labels_test)

x = MulticlassLibLinear()
kernel = GaussianKernel()

z = RelaxedTree()
z.set_labels(y_train)
z.set_machine_for_confusion_matrix(x)
z.set_kernel(kernel)

z.train(x_train)
predict = z.apply_multiclass(x_test)

eval = MulticlassAccuracy()
accuracy = eval.evaluate(predict, y_test)

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