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NEWS
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NEWS
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* Minor change
** Major change
1.3-6 (04/12/2017)
* optimized the code for computing the slores rule.
* added Slores screening without active cycling (-NAC) for logistic regression, research usage only.
* corrected BEDPP for elastic net.
* fixed a bug related to "exporting SSR-BEDPP".
1.3-5 (03/29/2017)
* redocumented using Roxygen2.
* registered native routines for faster and more stable performance.
1.3-4 (01/29/2017)
* fixed a bug related to `dfmax` option. (thanks you Florian Privé!)
1.3-3 (01/24/2017)
* fixed bugs related to KKT checking for elastic net. (thanks you Florian Privé!)
* added references for screening rules and the technical paper of biglasso package.
1.3-2 (01/16/2017)
* added screening methods without active cycling (-NAC) for comparison, research usage only.
* fixed a bug related to numeric comparison in Dome test.
1.3-1 (12/24/2016)
* fixed bug in SSR-Slores related to numeric equality comparison.
1.3-0 (12/15/2016)
* version 1.3-0 for CRAN submission.
1.2-6 (12/15/2016)
** added a newly proposed screening rule, SSR-Slores, for lasso-penalized logistic regression.
** added SSR-BEDPP for elastic-net-penalized linear regression.
1.2-5 (12/10/2016)
* updated README.md with benchmarking results.
* added tutorial (vignette).
1.2-4 (11/14/2016)
* added gaussian.cpp: solve lasso without screening, for research only.
* added tests.
1.2-3 (11/13/2016)
* changed convergence criteria of logistic regression to be the same as that in glmnet.
* optimized source code; preparing for CRAN submission.
* fixed memory leaks occurred on Windows.
1.2-2 (10/27/2016)
* added internal data set: the colon cancer data.
1.2-1 (10/18/2016)
** Implemented another new screening rule (SSR-BEDPP), also combining hybrid strong rule
with a safe rule (BEDPP).
** implemented EDPP rule with active set cycling strategy for linear regression.
* changed convergence criteria to be the same as that in glmnet.
1.1-2 (9/1/2016)
* fixed bugs occurred when some features have identical values for different
observations. These features are internally removed from model fitting.
1.1-1 (8/31/2016)
** Three sparse screening rules (SSR, EDPP, SSR-Dome) were implemented. Our
new proposed HSR-Dome combines HSR and Dome test for feature screening,
leading to even better performance as compared to 'glmnet'.
** OpenMP parallel computing was added to speedup single model fitting.
** Both exact Newton and majorization-minimization (MM) algorithm for logistic
regression were implemented. The latter could be faster, especially in
data-larger-than-RAM cases.
** Source code were rewritten in pure cpp.
* Sparse matrix representation was added using Armadillo library.
1.0-1 (3/1/2016)
** package ready for CRAN submission.