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biglasso 1.6.1
- Various internal fixes (see below)
- Updating references
- Fixing some broken links
- Removing an OMP directive that was causing stack imbalance
issues
- Improved CI testing
- Eliminating use of PROTECT in cpp code
- Some NAMESPACE changes
biglasso 1.6.0
- New: functions biglasso_fit() and biglasso_path(), which allow users
to turn off standardization and intercept
biglasso 1.5.2
- Update coercion for compatibility with Matrix 1.5
- Now using GitHub Actions instead of Travis for CI
biglasso 1.5.1
- Internal Cpp changes: initialize Xty, remove unused cutoff variable
(#48)
- Eliminate CV test against ncvreg (the two packages no longer use the
same approach (#47)
biglasso 1.5.0
- Update headers to maintain compatibility with new version of Rcpp
(#40)
biglasso 1.4-1
- changed R package maintainer to Chuyi Wang (wwaa0208@gmail.com)
- fixed bugs
- Add ‘auc’, ‘class’ options to cv.biglasso eval.metric
- predict.cv now predicts standard error over CV folds by default; set
‘grouped’ argument to FALSE for old behaviour.
- predict.cv.biglasso accepts ‘lambda.min’, ‘lambda.1se’ argument,
similar to predict.cv.glmnet()
biglasso 1.4-0
- adaptive screening methods were implemented and set as default when
applicable
- added sparse Cox regression
- removed uncompetitive screening methods and combined naming of
screening methods
- version 1.4-0 for CRAN submission
biglasso 1.3-7
- update email to personal email
- coef(cvfit) returns only nonzero cells, as a labelled vector
- set HSR rules as default
- option for non-standardization
biglasso 1.3-6
- 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”.
biglasso 1.3-5
- redocumented using Roxygen2.
- registered native routines for faster and more stable
performance.
biglasso 1.3-4
- fixed a bug related to
dfmax
option. (thanks you
Florian Privé!)
biglasso 1.3-3
- 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.
biglasso 1.3-2
- added screening methods without active cycling (-NAC) for
comparison, research usage only.
- fixed a bug related to numeric comparison in Dome test.
biglasso 1.3-1
- fixed bug in SSR-Slores related to numeric equality comparison.
biglasso 1.3-0
- version 1.3-0 for CRAN submission.
biglasso 1.2-6
- added a newly proposed screening rule, SSR-Slores, for
lasso-penalized logistic regression.
- added SSR-BEDPP for elastic-net-penalized linear regression.
biglasso 1.2-5
- updated README.md with benchmarking results.
- added tutorial (vignette).
biglasso 1.2-4
- added gaussian.cpp: solve lasso without screening, for research
only.
- added tests.
biglasso 1.2-3
- 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.
biglasso 1.2-2
- added internal data set: the colon cancer data.
biglasso 1.2-1
- 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.
biglasso 1.1-2
- fixed bugs occurred when some features have identical values for
different observations. These features are internally removed from model
fitting.
biglasso 1.1-1
- 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.
biglasso 1.0-1
- package ready for CRAN submission.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.