How to implement K Nearest neighbours using Shogun?

This recipe helps you to implement K Nearest neighbours using Shogun.

Recipe Objective

This recipe explains how we can implement K Nearest neighbors using Shogun.
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K Nearest neighbors

K Nearest neighbors compute data according to the majority of labels in the nearest neighborhood, based on some underlying distance function f(x,x1)

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

x = EuclideanDistance(x_train, x_train)

z = KNN(5, x, y_train)

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

eval = MulticlassAccuracy()

accuracy = eval.evaluate(predict, y_test)

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