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Abstract

Described systems and methods allow a computer security system to automatically classify target objects using a cascade of trained classifiers, for applications including malware, spam, and/or fraud detection. The cascade comprises several levels, each level including a set of classifiers. Classifiers are trained in the predetermined order of their respective levels. Each classifier is trained to divide a corpus of records into a plurality of record groups so that a substantial proportion (e.g., at least 95%, or all) of the records in one such group are members of the same class. Between training classifiers of consecutive levels of the cascade, a set of training records of the respective group is discarded from the training corpus. When used to classify an unknown target object, some embodiments employ the classifiers in the order of their respective levels.

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