Automatic selection of features for classification using genetic programming

Classifier design often involves the hand-selection of features, a process which relies on human experience and heuristics. We present the Evolutionary Pre-processor, a system which automatically extracts features for a range of classification problems. The Evolutionary Pre-processor uses genetic programming to allow useful features to emerge from the data, simulating the innovative work of the human designer. The Evolutionary Pre-processor improved the classification performance of a linear machine on two real-world problems. Although these problems are intuitively difficult to solve, the Evolutionary Pre-processor was able to generate complex feature sets. The classification results are comparable with those achieved by other classifiers