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Network Intrusion Detection is the most happening field of the network security research. It is a new kind of defense technology of the network security, used as a countermeasure to preserve data integrity and system availability during an intrusion. An ideal IDS system should be capable of evolving itself to identify not only known attacks but also unknown attacks. Algorithms based on Genetic Engineering...
Aiming at the prediction of protein solubility, four feature reduction methods are discussed in this paper, including Correlation coefficient method, Filter method, Relief method and Genetic method. With the Top 100 features discovered by genetic method, the best classifier achieves the accuracy of 86% and MCC of 0.7236 in Jackknife test. Moreover, further discussions about feature reduction and classifier...
In order to overcome the limitation on small sizes of gene datasets, many meta-classification methods which ensemble classifiers with different datasets have been developed. However, due to discrepancies of the characteristics within heterogeneous or cross-platform datasets, the number of common and significant genes is usually small. Instead of matching common genes between heterogeneous datasets,...
One of the most important issues in any association rule mining is the interpretation and evaluation of discovered rules. Thus, most algorithms employ the support-confidence framework for evaluating association and classification rules. Unfortunately, recent studies show that the support and confidence measures are insufficient for filtering out uninteresting association rules, for instance, even...
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