A Wrapper Feature Subset Selection Method Based on Randomized Search and Multilayer Structure
نویسندگان
چکیده
منابع مشابه
A New Wrapper Method for Feature Subset Selection
ANOVA decomposition is used as the basis for the development of a new wrapper feature subset selection method, in which functional networks are used as the induction algorithm. The performance of the proposed method was tested against several artificial and real data sets. The results obtained are comparable, and even better, in some cases, to those accomplished by other well-known methods, bei...
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Intrusion detection systems are designed to provide security in computer networks, so that if the attacker crosses other security devices, they can detect and prevent the attack process. One of the most essential challenges in designing these systems is the so called curse of dimensionality. Therefore, in order to obtain satisfactory performance in these systems we have to take advantage of app...
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In the wrapper approach to feature subset selection, a search for an optimal set of features is made using the induction algorithm as a black box. The estimated future performance of the algorithm is the heuristic guiding the search. Statistical methods for feature subset selection including forward selection, backward elimination, and their stepwise variants can be viewed as simple hill-climbi...
متن کاملA Parallel Genetic Algorithm Based Method for Feature Subset Selection in Intrusion Detection Systems
Intrusion detection systems are designed to provide security in computer networks, so that if the attacker crosses other security devices, they can detect and prevent the attack process. One of the most essential challenges in designing these systems is the so called curse of dimensionality. Therefore, in order to obtain satisfactory performance in these systems we have to take advantage of app...
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This work presents a hybrid wrapper/filter algorithm for feature subset selection that can use a combination of several quality criteria measures to rank the set of features of a dataset. These ranked features are used to prune the search space of subsets of possible features such that the number of times the wrapper executes the learning algorithm for a dataset with M features is reduced to O(...
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ژورنال
عنوان ژورنال: BioMed Research International
سال: 2019
ISSN: 2314-6133,2314-6141
DOI: 10.1155/2019/9864213