Low-Rank Sparse Feature Selection for Patient Similarity Learning

2016 ◽  
Author(s):  
Mengting Zhan ◽  
Shilei Cao ◽  
Buyue Qian ◽  
Shiyu Chang ◽  
Jishang Wei
Keyword(s):  
Feature Selection ◽  
Low Rank ◽  
Similarity Learning ◽  
Selection For ◽  
Sparse Feature Selection

scholarly journals Machine learning methods in the computational biology of cancer

2014 ◽  
Vol 470 (2167) ◽  
pp. 20140081 ◽  
Author(s):  
M. Vidyasagar
Keyword(s):  
Machine Learning ◽  
Ovarian Cancer ◽  
Feature Selection ◽  
Classification Problems ◽  
Open Problems ◽  
Machine Learning Methods ◽  
Selection For ◽  
Personalized Cancer Therapy ◽  
Personalized Cancer ◽  
Sparse Feature Selection

The objectives of this Perspective paper are to review some recent advances in sparse feature selection for regression and classification, as well as compressed sensing, and to discuss how these might be used to develop tools to advance personalized cancer therapy. As an illustration of the possibilities, a new algorithm for sparse regression is presented and is applied to predict the time to tumour recurrence in ovarian cancer. A new algorithm for sparse feature selection in classification problems is presented, and its validation in endometrial cancer is briefly discussed. Some open problems are also presented.

A novel low-rank hypergraph feature selection for multi-view classification

2017 ◽  
Vol 253 ◽  
pp. 115-121 ◽  
Author(s):  
Xiaohui Cheng ◽  
Yonghua Zhu ◽  
Jingkuan Song ◽  
Guoqiu Wen ◽  
Wei He
Keyword(s):  
Feature Selection ◽  
Low Rank ◽  
Selection For

scholarly journals Sparse feature selection for classification and prediction of metastasis in endometrial cancer

BMC Genomics ◽  
2017 ◽  
Vol 18 (S3) ◽  
Author(s):  
Mehmet Eren Ahsen ◽  
Todd P. Boren ◽  
Nitin K. Singh ◽  
Burook Misganaw ◽  
David G. Mutch ◽  
...  
Keyword(s):  
Feature Selection ◽  
Endometrial Cancer ◽  
Prediction Of Metastasis ◽  
Selection For ◽  
Sparse Feature Selection

Multiview Hessian Semisupervised Sparse Feature Selection for Multimedia Analysis

2017 ◽  
Vol 27 (9) ◽  
pp. 1947-1961 ◽  
Author(s):  
Caijuan Shi ◽  
Gaoyun An ◽  
Ruizhen Zhao ◽  
Qiuiqi Ruan ◽  
Qi Tian
Keyword(s):  
Feature Selection ◽  
Multimedia Analysis ◽  
Selection For ◽  
Sparse Feature Selection
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