How does the shareboost algorithm works in shogun?

This recipe explains how does the shareboost algorithm works in shogun.

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Recipe Objective

This recipe explains how does the shareboost algorithm works in shogun.
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ShareBoost

The shareboost algorithm uses a forward greedy selection approach and learns a multiclass predictor from a subset of shared features of the samples

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

s = ShareBoost(x_train, y_train, 2)
s.train()
z = RealSubsetFeatures(x_test, s.get_activeset())
predict = shareboost.apply_multiclass(z)

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

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