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Feature selection involves identifying a subset of the most useful features that produces compatible results as the original entire set of features. A feature selection algorithm may be evaluated from both the efficiency and effectiveness points of view. While the efficiency concerns the time required to find a subset of features, the effectiveness is(More)
The ever increasing growth of databases in the real time application is a major issue for the handling of large data. The data mining of the same is also a tedious task. The feature subset selection is a process for finding the irrelevant and redundant data and handling them. The proposed algorithm IFSSImproved Feature Subset Selection works in 2 major(More)
Great research work have been conducted towards Intrusion Detection Systems (IDSs) as well as feature selection. Feature selection applications have a great influence on decreasing development lead times and increasing product quality as well as proficiency. IDS guards a system from attack, misuse, and compromise. It can also screen network action. Network(More)
Feature subset selection is the process of choosing a subset of good features with respect to the target concept. A clustering based feature subset selection algorithm has been applied over software defect prediction data sets. Software defect prediction domain has been chosen due to the growing importance of maintaining high reliability and high quality(More)
Feature selection has been a productive field of research and development in data mining, machine learning and statistical pattern recognition, and is widely applied to many fields such as, image retrieval, genomic analysis and text categorization. Feature selection includes selecting the most useful features from the given data set. The feature selection(More)
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