1. A method of improving classification accuracy and reducing false positives in data mining, computer aided-detection, computer-aided diagnosis and artificial intelligence, the method comprising: choosing a training set from a set of training cases using systematic data scaling; and, creating a classifier based on the training set using a classification method, wherein the systematic data scaling method and the classification method produce the classifier thereby reducing false positives and improving classification accuracy.