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Some popular regression and classification methods include least angle regression, coordinate descent algorithm for penalty regression and support vector machine.

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Introduction

This projection depends on the armadillo matrix library which can be achieved in http://arma.sourceforge.net/download.html. The program mainly includes linear regression and classification. More detaily, there are ordinary least squares regression, least angle regression and coordinate descent algorithm for linear regression. About the linear classification, now, it only has support vector machine which is based on the SMO algorithm.

Reference

[1] Breheny, Patrick, and Jian Huang. "Coordinate descent algorithms for nonconvex penalized regression, with applications to biological feature selection." The annals of applied statistics 5.1 (2011): 232.

[2] Efron, Bradley, et al. "Least angle regression." The Annals of statistics 32.2 (2004): 407-499.

[3] Fan, Rong-En, Pai-Hsuen Chen, and Chih-Jen Lin. "Working set selection using second order information for training support vector machines." Journal of machine learning research 6.Dec (2005): 1889-1918.

[4] Platt, John. "Sequential minimal optimization: A fast algorithm for training support vector machines." (1998).

[5] Sanderson, Conrad, and Ryan Curtin. "Armadillo: a template-based C++ library for linear algebra." Journal of Open Source Software (2016).

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Some popular regression and classification methods include least angle regression, coordinate descent algorithm for penalty regression and support vector machine.

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