Deep search:Searching for "Feature selection" in 'KEYWORDGot 12 items.
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1Feature selection based on mutual information and redundancy-synergy coefficient
Author(s):YANG Sheng, GU Jun  Clicked:5936  Download:2568  Cited:4  <Full Text>
Journal of Zhejiang University Science  2004 Vol.5 No.11 P.1382-1391  DOI:10.1631/jzus.2004.1382
2Feature selection for face recognition: a memetic algorithmic approach
Author(s):Dinesh KUMAR, Shakti KUMAR, C. S. ...  Clicked:5321  Download:3230  Cited:6  <Full Text>
Journal of Zhejiang University Science A  2009 Vol.10 No.8 P.1140-1152  DOI:10.1631/jzus.A0820460
3A data-mining approach to biomarker identification from protein profiles using discrete stationary wavelet ...
Author(s):Hussain MONTAZERY-KORDY, Mohammad ...  Clicked:5745  Download:2790  Cited:5  <Full Text>
Journal of Zhejiang University Science B  2008 Vol.9 No.11 P.863-870  DOI:10.1631/jzus.B0820163
4A fast automatic recognition and location algorithm for fetal genital organs in ultrasound images
Author(s):Sheng TANG, Si-ping CHEN  Clicked:5551  Download:2827  Cited:0  <Full Text>
Journal of Zhejiang University Science B  2009 Vol.10 No.9 P.648-658  DOI:10.1631/jzus.B0930162
5Battle damage assessment based on an improved Kullback-Leibler divergence sparse autoencoder
Author(s):Zong-feng Qi, Qiao-qiao Liu, Jun W...  Clicked:3931  Download:1422  Cited:0  <Full Text>  <PPT> 1284
Frontiers of Information Technology & Electronic Engineering  2017 Vol.18 No.12 P.1991-2000  DOI:10.1631/FITEE.1601395
6A new feature selection method for handling redundant information in text classification
Author(s):You-wei Wang, Li-zhou Feng  Clicked:4290  Download:1814  Cited:0  <Full Text>  <PPT> 1227
Frontiers of Information Technology & Electronic Engineering  2018 Vol.19 No.2 P.221-234  DOI:10.1631/FITEE.1601761
7A feature selection approach based on a similarity measure for software defect prediction
Author(s):Qiao Yu, Shu-juan Jiang, Rong-cun ...  Clicked:5048  Download:2121  Cited:0  <Full Text>  <PPT> 1259
Frontiers of Information Technology & Electronic Engineering  2017 Vol.18 No.11 P.1744-1753  DOI:10.1631/FITEE.1601322
8An effective fault prediction model developed using an extreme learning machine with various kernel methods
Author(s):Lov Kumar, Anand Tirkey, Santanu-K...  Clicked:4272  Download:2017  Cited:0  <Full Text>  <PPT> 1106
Frontiers of Information Technology & Electronic Engineering  2018 Vol.19 No.7 P.864-888  DOI:10.1631/FITEE.1601501
9Unsupervised feature selection via joint local learning and group sparse regression
Author(s):Yue Wu, Can Wang, Yue-qing Zhang, ...  Clicked:5366  Download:1370  Cited:0  <Full Text>  <PPT> 1176
Frontiers of Information Technology & Electronic Engineering  2019 Vol.20 No.4 P.538-553  DOI:10.1631/FITEE.1700804
10FAAD: an unsupervised fast and accurate anomaly detection method for a multi-dimensional sequence over data...
Author(s):Bin Li, Yi-jie Wang, Dong-sheng Ya...  Clicked:3612  Download:1651  Cited:0  <Full Text>  <PPT> 1423
Frontiers of Information Technology & Electronic Engineering  2019 Vol.20 No.3 P.388-404  DOI:10.1631/FITEE.1800038
11A software defect prediction method with metric compensation based on feature selection and transfer learning
Author(s):Jinfu CHEN, Xiaoli WANG, Saihua CA...  Clicked:384  Download:379  Cited:0  <Full Text>  <PPT> 28
Frontiers of Information Technology & Electronic Engineering  2022 Vol.23 No.5 P.715-731  DOI:10.1631/FITEE.2100468
12Feature-selection techniques for microarray dataset: a comprehensive review, taxonomy, and future directions
Author(s):K. BALAKRISHNAN, R. DHANALAKSHMI  Clicked:46  Download:49  Cited:0  <Full Text>
Frontiers of Information Technology & Electronic Engineering  1998 Vol.-1 No.-1 P.  DOI:10.1631/FITEE.2100569
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