Separability is not the best goal for machine learning

8 Jul 2018Wlodzislaw Duch

Neural networks use their hidden layers to transform input data into linearly separable data clusters, with a linear or a perceptron type output layer making the final projection on the line perpendicular to the discriminating hyperplane. For complex data with multimodal distributions this transformation is difficult to learn... (read more)

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