A Hybrid Method of Feature Subset Selection
نویسندگان
چکیده
منابع مشابه
A 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...
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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pathological changes within an organ can be reflected as proteomic patterns in biological fluids such as plasma, serum, and urine. the surface-enhanced laser desorption and ionization time-of-flight mass spectrometry (seldi-tof ms) has been used to generate proteomic profiles from biological fluids. mass spectrometry yields redundant noisy data that the most data points are irrelevant features ...
متن کاملA hybrid wrapper / filter approach for feature subset selection
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: Journal of Japan Society for Fuzzy Theory and Systems
سال: 2002
ISSN: 0915-647X,2432-9932
DOI: 10.3156/jfuzzy.14.6_648