Computer Science ›› 2018, Vol. 45 ›› Issue (12): 182-186.doi: 10.11896/j.issn.1002-137X.2018.12.029
• Artificial Intelligence • Previous Articles Next Articles
PENG Xiao-bing1,2, ZHU Yu-quan1
CLC Number:
[1]BUTT K J.A study of feature selection algorithms for accuracy estimation.Ajr American Journal of Roentgenology,2012,149(6):1155-1160. [2]IQBAL R A.Empirical Learning Aided by Weak DomainKnowledge in the Form of Feature Importance[C]∥International Conference on Multimedia and Signal Processing.IEEE Computer Society,2011:126-130. [3]ZHANG L,WANG Z.Ontology-based Clustering Algorithmwith Feature Weights.Journal of Computational Information Systems,2010,6(9):2959-2966. [4]WANG T H,TIAN S F,HUANG H K.Feature Weighted Support Vector Machine.Journal of Electronics & Information Technology,2009,31(3):514-518.(in Chinese) 汪廷华,田盛丰,黄厚宽.特征加权支持向量机.电子与信息学报,2009,31(3):514-518. [5]WALTON S,HASSAN O,MORGAN K,et al.Modified cuckoo search:A new gradient free optimisation algorithm[J].Chaos,Solitons & Fractals,2011,44(9):710-718. [6]SHANNON C E.A mathematical theory of communication.Bell System Techical Journal,1948,27(3):379-423,623-656. [7]MALIK H H,FRADKIN D,MOERCHEN F.Single pass text classification by direct feature weighting.Knowledge & Information Systems,2011,28(1):79-98. [8]GIVEKI D,SALIMI H,BAHMANYAR G R,et al.Automatic Detection of Diabetes Diagnosis using Feature Weighted Support Vector Machines based on Mutual Information and Modified Cuckoo Search.Computer Science,2012,abs/1201.2173. [9]XING H J,HA M H,HU B G,et al.Linear feature-weighted support vector machine[J].Fuzzy Information and Engineering 2009,1(3):289-305. [10]SHANNON C E,WEAVER W.The Mathematical Theory of Communication.Urbana:University of Illinois Press,1949. [11]CHEN Y,HAO Y.A Feature Weighted Support Vector Ma-chine and K-Nearest Neighbor Algorithm for Stock Market Indices Prediction.Expert Systems with Applications,2017,80:340-355. [12]IQBAL R A.Using Feature Weights to Improve Performance of Neural Networks.http://arXiv:1101.4918. [13]LIU L,ZHANG J,LI P,et al.A Label Correlation Based Weighting Feature Selection Approach for Multi-label Data.Berlin:Springer International Publishing,2016:369-379. [14]WANG Y,LI T.Feature and Sample Weighted Support Vector Machine∥Knowledge Engineering and Management.Springer Berlin Heidelberg,2011:365-371. [15]GAO Y L,LIU Y X.An improved feature-weighted methodbased on K-NN[C]∥Control Conference.IEEE,2016:6950-6956. [16]WOLFEL M,EKENEL H K.Feature weighted mahalanobisdistance:Improved robustness for Gaussian classifiers[C]∥13th European Signal Processing Conference.IEEE,2005:2018-2021. [17]JIA G,ZHAO H,PAN Z,et al.Local Feature Weighting for Data Classification∥ransactions on Edutainment XIII.Sprin-ger Berlin Heidelberg,2017:293-302. |
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