A Fast Feature Selection Framework and Method

doi:10.13190/j.jbupt.2018-151

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2019, Vol. 42 ›› Issue (3): 127-132.doi: 10.13190/j.jbupt.2018-151

• Reports • Previous Articles

A Fast Feature Selection Framework and Method

QIU Li-ke¹, LIU Jing², SUN Zhong-wei³, ZHAO Yang-fan⁴

1. Information Management Department, Shandong Foreign Trade Vocational College, Qingdao 266100, China;
2. Science and Information College, Qingdao Agricultural University, Qingdao 266100, China;
3. School of Information and Control Engineering, Qingdao University of Technology, Qingdao 266100, China;
4. Comprehensive Planning Office, Shandong Qingdao Tobacco Copany Limited, Qingdao 266100, China

Received:2018-07-04 Online:2019-06-28 Published:2019-06-20

Abstract

Abstract: Aiming at the imbalance between accuracy and computational efficiency in feature selection, a fast feature selection framework (FFFS) is proposed. Based on this framework, a fast feature selection algorithm, MRMR-SFS, is proposed. The minimum redundancy maximum relevance (MRMR) method is used to select the candidate features, and sequential forward selection (SFS) method is used to verify the performance of the candidate features as well. It improves the calculation efficiency by limiting the number of iterations. Comparison experiments with the MRMR, SFS and a filter-dominating hybrid sequential floating forward selection algorithms demonstrate that MRMR-SFS can balance the accuracy and computational efficiency well.

Key words: feature selection, filter, wrapper, hybrid, performance prediction, correlation coefficient

CLC Number:

TP181

QIU Li-ke, LIU Jing, SUN Zhong-wei, ZHAO Yang-fan. A Fast Feature Selection Framework and Method[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2019, 42(3): 127-132.

[1]	LIU Jinming, ZHANG Biling, ZHANG Yuyan. Adaptive federated filtering algorithm based on multi-sensor redundant data cooperative tracking [J]. Journal of Beijing University of Posts and Telecommunications, 2023, 46(4): 21-26.
[2]	ZHANG Yifan, WU Yongle, WANG Qing, WANG Weimin. Design of a High-Selectivity Absorptive Dual-Band Balanced Bandpass Filter [J]. Journal of Beijing University of Posts and Telecommunications, 2023, 46(4): 1-8.
[3]	XIN Yu, XU You, ZHANG Huaijin, BAO Tong, KONG Dejin. High Time-Frequency Efficiency Generalized Filter Banks Frequency Division Multiplexing Modulation Scheme [J]. Journal of Beijing University of Posts and Telecommunications, 2023, 46(4): 109-115.
[4]	LIU Yang, TENG Yinglei, NIU Tao, ZHI Jialin. Filter Pruning Algorithm Based on Deep Reinforcement Learning [J]. Journal of Beijing University of Posts and Telecommunications, 2023, 46(3): 31-36.
[5]	WU Jin, ZHAO Bo, WEN Heng, WANG Yu. A Graph Neural Network Accelerator Optimization Research on Heterogeneous Architecture [J]. Journal of Beijing University of Posts and Telecommunications, 2023, 46(3): 19-24.
[6]	SUN Yanhua, QIAO Lan, WANG Zhuwei, LI Meng, SI Pengbo. Hybrid Beamforming for Intelligent Reflecting Surface Assisted MIMO System [J]. Journal of Beijing University of Posts and Telecommunications, 2023, 46(3): 7-12.
[7]	ZHANG Haoge, SHAO Yubin, LONG Hua, PENG Yi, ZHOU Dachun. Language Recognition Based on Log Gammatone-Scale Filter Bank Energies Spectrograms [J]. Journal of Beijing University of Posts and Telecommunications, 2023, 46(1): 38-43.
[8]	LIU Jinming, ZHANG Yuyan, ZHANG Biling. Trajectory Estimation Algorithm for Unmanned Aerial Vehicle Based on LSTM-KF [J]. Journal of Beijing University of Posts and Telecommunications, 2022, 45(5): 121-128.
[9]	SHI Zicheng, LI Xin, TANG Ying, HUANG Shanguo. Optical Packet Filtering System Based on All-Optical Pattern Matching [J]. Journal of Beijing University of Posts and Telecommunications, 2022, 45(3): 96-101.
[10]	HUO Yuanlian, GONG Qi, QI Yongfeng, AN Yaqi. Adaptive Kernel RBFNN Based on Normalized Least Mean Square Algorithm [J]. Journal of Beijing University of Posts and Telecommunications, 2022, 45(2): 29-35.
[11]	LI Xiaohui, WANG Xianwen, FAN Tao, LIU Jiawen, WAN Hongjie. A High-Performance Downlink Synchronization Algorithm Based on Convolutional Neural Network for 5G Systems [J]. Journal of Beijing University of Posts and Telecommunications, 2022, 45(2): 117-123.
[12]	ZHANG Jingtian, MA Ying, WENG Xun, SUN Zhuangzhi, ZHANG Jilong. Optimization of Lifts Scheduling for Four-Way Shuttle Systems [J]. Journal of Beijing University of Posts and Telecommunications, 2022, 45(1): 19-25,81.
[13]	HUO Yuanlian, LIAN Peijun, QI Yongfeng, WANG Danfeng. A New Fast Convex Combination Affine Projection Sign Algorithm for S-type Functions [J]. Journal of Beijing University of Posts and Telecommunications, 2022, 45(1): 102-107.
[14]	SONG Cheng, JIN Tong, HE Jun-yi. A Multi-Value Prediction Location Privacy Protection Mechanism [J]. Journal of Beijing University of Posts and Telecommunications, 2021, 44(6): 103-108.
[15]	YANG Yu-hao, WU Yong-le, WANG Wei-min. Design and Realization of a Filtering Gysel Power Divider [J]. Journal of Beijing University of Posts and Telecommunications, 2021, 44(6): 122-128.

A Fast Feature Selection Framework and Method

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments