Comparison of Different Methods for the Binary Classification of Points in the Plane

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This Demonstration contains test datasets of points that are labeled red or blue depending on their positions in the plane. A classifier can be trained with different methods to learn the dependence of the color label from the coordinates of the point. To this end, a set of points (the training set) together with their labels is shown to the classifier. After training, the classifier must predict the labels of a different set of points (the test set). The accuracy of the classification on the test set depends on the size of the training set and the method used.

Contributed by: Frank Brechtefeld (December 2016)
Open content licensed under CC BY-NC-SA


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