Fast Maximum Entropy Machine for Big Imbalanced Datasets
Fast Maximum Entropy Machine for Big Imbalanced Datasets is a scholarly work, published in 2018 in ''Journal of Communications and Information Networks''. The main subjects of the publication include kernel, data mining, artificial intelligence, Entropy, computer science, facial recognition system, support vector machine, binary classification, big data, machine learning, pattern recognition, algorithm, and principle of maximum entropy. The authors present a fast maximum entropy machine (MEM) combined with a synthetic minority over-sampling technique for handling binary classification problems with high imbalance ratios, large numbers of data samples, and medium/large numbers of features.