How to implement Multiclass Linear Machine using Shogun?

This recipe helps you to implement Multiclass Linear Machine using Shogun.

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Recipe Objective

This recipe explains how we can implement a Multi-class Linear Machine using Shogun.
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Multi-class Linear Machine

We have extended the use of linear machines in multi-class datasets by forming generic multiclass classifiers with ensembles of binary classifiers.

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

c = LibLinear()
s = MulticlassOneVsOneStrategy()
z = LinearMulticlassMachine(s, x_train, c, y_train)

z.train()
predict = mc_classifier.apply_multiclass(x_test)
eval = MulticlassAccuracy()
accuracy = eval.evaluate(predict, y_test)

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