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Prikaz objav, dodanih na december, 2013

Border Pairs Method—constructive MLP learning classification algorithm

Border Pairs Method (BPM) is a new constructive method for supervised learning of multilayer perceptron (MLP), which calculates, values of weights and biases directly from the geometry of learning patterns.

To determine BPM’s capabilities, we compared it with three other supervised machine learning methods: Backpropagation , SVM  and Decision Trees. The comparison were made on six databases: XOR, Triangle, Iris, Pen-Based Recognition of Handwritten Digits, Online Pen-Based Recognition of Handwritten Digits and synthetically generated noisy data. Border Pairs Method found near minimal MLP architecture in all described cases. For classification of the Iris Setosa only two border pairs (only four patterns out of 150) were enough for learning the whole data set correctly. In the classification of ‘Pen-Based Recognition of Handwritten Digits’ dataset only 200 learning patterns were used for learning. The BPM correctly identified more than 95% from 3498 handwritten digits, which did not part…