Using mixed kernel support vector machine to improve the predictive accuracy of genome selection1

Author:

Wang Jinbu,Zong Wencheng,Shi Liangyu,Li Mianyan,Li Jia,Ren Deming,Zhao Fuping,Wang Lixian,Wang Ligang

Publisher

Elsevier BV

Reference61 articles.

1. Deep learning versus parametric and ensemble methods for genomic prediction of complex phenotypes;Abdollahi-Arpanahi;Genet Sel Evol,2020

2. On the Surprising Behavior of Distance Metrics in High Dimensional Space;Aggarwal,2001

3. Genome-enabled prediction of reproductive traits in Nellore cattle using parametric models and machine learning methods;Alves;Anim Genet,2021

4. KCRR: a nonlinear machine learning with a modified genomic similarity matrix improved the genomic prediction efficiency;An;Brief Bioinform,2021

5. A Novel SVM based CSSFFS Feature Selection Algorithm for Detecting Breast Cancer;Aruna;international journal of computer applications,2013

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