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

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

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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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