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DALASS: Variable selection in discriminant analysis via the LASSO

Trendafilov, Nickolay T. and Jolliffe, Ian T. (2007). DALASS: Variable selection in discriminant analysis via the LASSO. Computational Statistics and Data Analysis, 51(8) pp. 3718–3736.

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The objective of DALASS is to simplify the interpretation of Fisher’s discriminant function coefficients. The DALASS problem—discriminant analysis (DA) modified so that the canonical variates satisfy the LASSO constraint—is formulated as a dynamical system on the unit sphere. Both standard and orthogonal canonical variates are considered. The globally convergent continuous-time algorithms are illustrated numerically and applied to some well-known data sets.

Item Type: Journal Article
ISSN: 0167-9473
Keywords: Canonical variates; Orthogonal canonical variates; LASSO constraint; Penalty function; Continuous-time constrained optimization;Steepest ascent vector flows on manifolds
Academic Unit/Department: Mathematics, Computing and Technology > Mathematics and Statistics
Mathematics, Computing and Technology
Item ID: 7277
Depositing User: Nickolay Trendafilov
Date Deposited: 11 Apr 2007
Last Modified: 14 Jan 2016 16:29
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