Semi-supervised sparse feature selection via graph Laplacian based scatter matrix for regression problems

Razieh Sheikhpour; Mehdi Agha Sarram; Elnaz Sheikhpour

doi:10.1016/j.ins.2018.08.035

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Semi-supervised sparse feature selection via graph Laplacian based scatter matrix for regression problems

Razieh Sheikhpour Mehdi Agha Sarram Elnaz Sheikhpour

Year: 2018 Journal: Information Sciences Vol: 468 Pages: 14-28 Publisher: Elsevier BV

DOI: 10.1016/j.ins.2018.08.035

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Keywords:

Feature selection Laplacian matrix Graph Regression Pattern recognition (psychology) Artificial intelligence Computer science Regularization (linguistics) Semi-supervised learning ENCODE Feature (linguistics) Regular polygon Supervised learning Convex optimization Mathematics Machine learning Theoretical computer science Artificial neural network Statistics

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Semi-supervised sparse feature selection via graph Laplacian based scatter matrix for regression problems

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