Simple one-pass algorithm for penalized linear regression with cross-validation on MapReduce

28 Jun 2013Kun Yang

In this paper, we propose a one-pass algorithm on MapReduce for penalized linear regression \[f_\lambda(\alpha, \beta) = \|Y - \alpha\mathbf{1} - X\beta\|_2^2 + p_{\lambda}(\beta)\] where $\alpha$ is the intercept which can be omitted depending on application; $\beta$ is the coefficients and $p_{\lambda}$ is the penalized function with penalizing parameter $\lambda$. $f_\lambda(\alpha, \beta)$ includes interesting classes such as Lasso, Ridge regression and Elastic-net... (read more)

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