PNrule: A New Framework for Learning Classifier Models in Data Mining (A Case-Study in Network Intrusion Detection).

摘要: Learning classifier models is an important problem in data mining. Observations from the real world are often recorded as a set of records, each characterized by multiple attributes. Associated with record categorical attribute called class. Given training records known class labels, to learn model for terms other The goal use this predict any given such that certain objective function based on predicted and actual classes optimized. Traditionally, has been minimize number misclassified records; i.e. maximize accuracy. Various techniques exist today build models[11]. Although no single technique proven be best all situations, rule-based especially popular domain This can contributed easy interpretability rules humans, competitive performance exhibited many application domains.