GENERATION AND EFFECTIVENESS EVALUATION OF A MULTI-FEATURE CLASSIFICATION SYSTEM USING GENETIC ALGORITHMS

摘要

The features that are presented to an evolutionary algorithm (160) are preprocessed to generate combination features (141) that may be more efficient in distinguishing among classifications than the individual features (110) that comprise the combination feature. An initial set of features is defined that includes a large number of potential features, including the generated features that are combinations of other features. These features include, words used in a collection of content material that has been previously classified, as well as combination features based on these features. This pool of original features (110) and combination features (141) are provided to an evolutionary algorithm for a subsequent evaluation, generation, and determination of the best subset of features (131') to use for classification. In this evaluation and generation process, each combination feature is processed as an independent feature, independent of the features that were used, or not used, to form the combination feature. The resultant best performing subset (131') is subsequently used to characterize new content material for automated classification.