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There are 25014 results for: content related to: Combination of kernel PCA and linear support vector machine for modeling a nonlinear relationship between bioactivity and molecular descriptors

  1. Prediction model for increasing propylene from FCC gasoline secondary reactions based on Levenberg–Marquardt algorithm coupled with support vector machines

    Journal of Chemometrics

    Volume 24, Issue 9, September 2010, Pages: 574–583, Xiaowei Zhou, Bolun Yang, Chunhai Yi, Jun Yuan and Longyan Wang

    Version of Record online : 18 JUL 2010, DOI: 10.1002/cem.1317


    Intelligent Systems in Accounting, Finance and Management

    Volume 19, Issue 4, October/December 2012, Pages: 229–246, Jie Sun

    Version of Record online : 11 OCT 2012, DOI: 10.1002/isaf.1331

  3. A Novel and Principled Multiclass Support Vector Machine

    International Journal of Intelligent Systems

    Volume 30, Issue 10, October 2015, Pages: 1047–1082, Ping Ling and Xiangsheng Rong

    Version of Record online : 21 APR 2015, DOI: 10.1002/int.21718

  4. Support vector machines in engineering: an overview

    Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery

    Volume 4, Issue 3, May/June 2014, Pages: 234–267, S. Salcedo-Sanz, J. L. Rojo-Álvarez, M. Martínez-Ramón and G. Camps-Valls

    Version of Record online : 28 APR 2014, DOI: 10.1002/widm.1125

  5. Magnetic resonance brain image classification based on weighted-type fractional Fourier transform and nonparallel support vector machine

    International Journal of Imaging Systems and Technology

    Volume 25, Issue 4, December 2015, Pages: 317–327, Yu-Dong Zhang, Shufang Chen, Shui-Hua Wang, Jian-Fei Yang and Preetha Phillips

    Version of Record online : 24 NOV 2015, DOI: 10.1002/ima.22144

  6. Selecting quasar candidates using a support vector machine classification system

    Monthly Notices of the Royal Astronomical Society

    Volume 425, Issue 4, 1 October 2012, Pages: 2599–2609, Nanbo Peng, Yanxia Zhang, Yongheng Zhao and Xue-bing Wu

    Version of Record online : 31 AUG 2012, DOI: 10.1111/j.1365-2966.2012.21191.x


    Computational Intelligence

    Volume 29, Issue 2, May 2013, Pages: 331–356, Kai Ming Ting, Lian Zhu and Jonathan R. Wells

    Version of Record online : 12 JUN 2012, DOI: 10.1111/j.1467-8640.2012.00441.x

  8. A variance reduction framework for stable feature selection

    Statistical Analysis and Data Mining: The ASA Data Science Journal

    Volume 5, Issue 5, October 2012, Pages: 428–445, Yue Han and Lei Yu

    Version of Record online : 29 JUN 2012, DOI: 10.1002/sam.11152

  9. A Penalized Wrapper Method for Screening Main Effects and Interactions in Supersaturated Designs

    Quality and Reliability Engineering International

    Volume 31, Issue 8, December 2015, Pages: 1423–1435, C. Koukouvinos and C. Parpoula

    Version of Record online : 30 JUN 2014, DOI: 10.1002/qre.1679

  10. You have full text access to this OnlineOpen article
    Least square support vector and multi-linear regression for statistically downscaling general circulation model outputs to catchment streamflows

    International Journal of Climatology

    Volume 33, Issue 5, April 2013, Pages: 1087–1106, D. A. Sachindra, F. Huang, A. Barton and B. J. C. Perera

    Version of Record online : 27 APR 2012, DOI: 10.1002/joc.3493

  11. More robust and better: a multiple kernel support vector machine ensemble approach for traffic incident detection

    Journal of Advanced Transportation

    Volume 48, Issue 7, November 2014, Pages: 858–875, Jianli Xiao, Xiang Gao, Qing-Jie Kong and Yuncai Liu

    Version of Record online : 6 MAY 2013, DOI: 10.1002/atr.1231

  12. Online training on a budget of support vector machines using twin prototypes

    Statistical Analysis and Data Mining: The ASA Data Science Journal

    Volume 3, Issue 3, June 2010, Pages: 149–169, Zhuang Wang and Slobodan Vucetic

    Version of Record online : 12 MAY 2010, DOI: 10.1002/sam.10075

  13. You have free access to this content
    Approximating SWAT Model Using Artificial Neural Network and Support Vector Machine

    JAWRA Journal of the American Water Resources Association

    Volume 45, Issue 2, April 2009, Pages: 460–474, Xuesong Zhang, Raghavan Srinivasan and Michael Van Liew

    Version of Record online : 25 MAR 2009, DOI: 10.1111/j.1752-1688.2009.00302.x

  14. Loop-length-dependent SVM prediction of domain linkers for high-throughput structural proteomics

    Peptide Science

    Volume 92, Issue 1, 2009, Pages: 1–8, Teppei Ebina, Hiroyuki Toh and Yutaka Kuroda

    Version of Record online : 9 OCT 2008, DOI: 10.1002/bip.21105

  15. Robust Support Vector Machines with Low Test Time

    Computational Intelligence

    Volume 31, Issue 4, November 2015, Pages: 619–641, Yahya Forghani and Hadi Sadoghi Yazdi

    Version of Record online : 15 APR 2014, DOI: 10.1111/coin.12039

  16. A real-time model based on optimized least squares support vector machine for industrial polypropylene melt index prediction

    Journal of Chemometrics

    Volume 30, Issue 6, June 2016, Pages: 324–331, Miao Zhang and Xinggao Liu

    Version of Record online : 8 APR 2016, DOI: 10.1002/cem.2795


    Computational Intelligence

    Volume 30, Issue 2, May 2014, Pages: 285–315, Tingting Mu, Makoto Miwa, Junichi Tsujii and Sophia Ananiadou

    Version of Record online : 6 AUG 2012, DOI: 10.1111/j.1467-8640.2012.00452.x

  18. Relaxed constraints support vector machine

    Expert Systems

    Volume 29, Issue 5, November 2012, Pages: 506–525, Mostafa Sabzekar, Hadi Sadoghi Yazdi and Mahmoud Naghibzadeh

    Version of Record online : 2 SEP 2011, DOI: 10.1111/j.1468-0394.2011.00611.x

  19. You have full text access to this OnlineOpen article
    Surface vector mapping of magnetic anomalies over the Moon using Kaguya and Lunar Prospector observations

    Journal of Geophysical Research: Planets

    Volume 120, Issue 6, June 2015, Pages: 1160–1185, Hideo Tsunakawa, Futoshi Takahashi, Hisayoshi Shimizu, Hidetoshi Shibuya and Masaki Matsushima

    Version of Record online : 23 JUN 2015, DOI: 10.1002/2014JE004785

  20. Feature Selection for Support Vector Machine in the Study of Financial Early Warning System

    Quality and Reliability Engineering International

    Volume 30, Issue 6, October 2014, Pages: 867–877, Jingxiang Li, Yichen Qin, Danhui Yi, Yang Li and Ye Shen

    Version of Record online : 30 JUN 2014, DOI: 10.1002/qre.1684