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Feature selection for unsupervised learning through local learning.

, , , , and . Pattern Recognition Letters, (2015)

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Pathway-Based Feature Selection Algorithm for Cancer Microarray Data., , , , and . Adv. Bioinformatics, (2009)Improved breast cancer prognosis through the combination of clinical and genetic markers., , , , and . Bioinformatics, 23 (1): 30-37 (2007)A Feature Selection Algorithm Capable of Handling Extremely Large Data Dimensionality., , and . SDM, page 530-540. SIAM, (2008)Fast Implementation of ℓ1Regularized Learning Algorithms Using Gradient Descent Methods., , , , and . SDM, page 862-871. SIAM, (2010)Combining nomogram and microarray data for predicting prostate cancer recurrence., , and . BIBE, page 1-7. IEEE, (2008)Feature selection for unsupervised learning through local learning., , , , and . Pattern Recognition Letters, (2015)Predicting Breast Cancer Metastasis by Integrating Both Clinical and Genetic Markers., and . BIOCOMP, page 229-235. CSREA Press, (2007)Dimensionality Reduction Via Graph Structure Learning., , , and . KDD, page 765-774. ACM, (2015)Feature Selection for Nonlinear Regression and its Application to Cancer Research., , and . SDM, page 73-81. SIAM, (2015)SimplePPT: A Simple Principal Tree Algorithm., , , , and . SDM, page 792-800. SIAM, (2015)