Skip to content

HTTPS clone URL

Subversion checkout URL

You can clone with HTTPS or Subversion.

Download ZIP
Fetching contributors…

Cannot retrieve contributors at this time

41 lines (31 sloc) 1.279 kb
What the l1 addition is
=======================
A slight modification that allows l1 regularized LikelihoodModel.
Regularization is handled by a fit_regularized method.
Main Files
==========
l1_demo/demo.py
$ python demo.py --get_l1_slsqp_results logit
does a quick demo of the regularization using logistic regression.
l1_demo/sklearn_compare.py
$ python sklearn_compare.py
Plots a comparison of regularization paths. Modify the source to use
different datasets.
statsmodels/base/l1_cvxopt.py
fit_l1_cvxopt_cp()
Fit likelihood model using l1 regularization. Use the CVXOPT package.
Lots of small functions supporting fit_l1_cvxopt_cp
statsmodels/base/l1_slsqp.py
fit_l1_slsqp()
Fit likelihood model using l1 regularization. Use scipy.optimize
Lots of small functions supporting fit_l1_slsqp
statsmodels/base/l1_solvers_common.py
Common methods used by l1 solvers
statsmodels/base/model.py
Likelihoodmodel.fit()
3 lines modified to allow for importing and calling of l1 fitting functions
statsmodels/discrete/discrete_model.py
L1MultinomialResults class
Child of MultinomialResults
MultinomialModel.fit()
3 lines re-directing l1 fit results to the L1MultinomialResults class
Jump to Line
Something went wrong with that request. Please try again.