Add to ORKGCopyright 2013 c ⃝ Vahid Chahkandi, Mahdi Yaghoobi and Gelareh Veisi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Feature selection plays an important role in data mining and pattern recognition, especially in the case of large scale data. Feature selection is done due to large amount of noise and irrelevant features in the original data set. Hence, the efficiency of learning algorithms will increase incredibly if these irrelevant data are removed by this procedure. A novel approach for feature selection is introduced in this paper using CHABCF, (Chaotic Artificial Bee Col...
"Dimensionality" is one of the major problems which affect the quality of learning process in most o...
Feature selection is a process that provides model extraction by specifying necessary or related fea...
Feature selection is the basic pre-processing task of eliminating irrelevant or redundant features t...
© 2015 IEEE. Feature selection often involves two conflicting objectives of minimizing the feature s...
Abstract With the development of artificial intelligence, numerous researchers are attracted to stud...
For improving the classification accuracy of the classifier, a novel classification methodology base...
For improving the classification accuracy of the classifier, a novel classification methodology base...
For improving the classification accuracy of the classifier, a novel classification methodology base...
The paper was presented in the 2nd International Conference on Intelligent Systems, Metaheuristics &...
The feature subset selection, along with the parameters of classifier significantly influences the c...
Feature selection (FS) is a challenging problem that attracted the attention of many researchers. F...
Feature selection has two major conflicting aims, i.e., to maximize the classification performance a...
In this work, performance of the Artificial Bee Colony Algorithm which is a recently proposed algori...
Feature selection has two major conflicting aims, i.e., to maximize the classification performance a...
Feature selection has two major conflicting aims, i.e., to maximize the classification performance a...
"Dimensionality" is one of the major problems which affect the quality of learning process in most o...
Feature selection is a process that provides model extraction by specifying necessary or related fea...
Feature selection is the basic pre-processing task of eliminating irrelevant or redundant features t...
© 2015 IEEE. Feature selection often involves two conflicting objectives of minimizing the feature s...
Abstract With the development of artificial intelligence, numerous researchers are attracted to stud...
For improving the classification accuracy of the classifier, a novel classification methodology base...
For improving the classification accuracy of the classifier, a novel classification methodology base...
For improving the classification accuracy of the classifier, a novel classification methodology base...
The paper was presented in the 2nd International Conference on Intelligent Systems, Metaheuristics &...
The feature subset selection, along with the parameters of classifier significantly influences the c...
Feature selection (FS) is a challenging problem that attracted the attention of many researchers. F...
Feature selection has two major conflicting aims, i.e., to maximize the classification performance a...
In this work, performance of the Artificial Bee Colony Algorithm which is a recently proposed algori...
Feature selection has two major conflicting aims, i.e., to maximize the classification performance a...
Feature selection has two major conflicting aims, i.e., to maximize the classification performance a...
"Dimensionality" is one of the major problems which affect the quality of learning process in most o...
Feature selection is a process that provides model extraction by specifying necessary or related fea...
Feature selection is the basic pre-processing task of eliminating irrelevant or redundant features t...