Mutual Information and Gamma Test for Input Selection
Nima Reyhani, Hao Jin, Yongnan Ji, Amaury Lendasse · 2005
Abstract. In this paper, input selection is performed using two different approaches. The first approach is based on the Gamma test. This test estimates the mean square error (MSE) that can be achieved without overfitting. The best set of inputs is the one that minimises the result of the Gamma test. The second method estimates the Mutual Information between a set of inputs and the output. The best set of inputs is the one that maximises the Mutual Information. Both methods are applied for the selection of the inputs for function approximation and time series prediction problems. 1