LargeRegression (1.0)

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Large Regressions.

Uses gradient descent to minimize the sum of squared residuals for the regression problem. Can include an L2 penalty on the coefficient matrix. This function is very useful when there is an initial guess of what B should be in Y = XB. In general, this function performs faster than R's lm function. GPU acceleration can be used to make this function extremely fast. This package suggests cudaMatrixOps, which is not on CRAN but can be downloaded at

Maintainer: Unknown
Author(s): Jeffrey Wong

License: GPL

Uses: Matrix

Released over 8 years ago.



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