up

Author: idc9

ya_glm/backends/cvxpy/glm_solver.py

@@ -3,6 +3,7 @@
 from time import time
 
 from ya_glm.utils import clip_zero
+from ya_glm.processing import process_weights_group_lasso
 from ya_glm.cvxpy.penalty import lasso_penalty, ridge_penalty,\
      tikhonov_penalty,  multi_task_lasso_penalty, group_lasso_penalty
 from ya_glm.cvxpy.loss_functions import lin_reg_loss, log_reg_loss,\
@@ -183,6 +184,9 @@ def setup_problem(X, y,
     if lasso_pen is not None:
 
         if groups is not None:
+            lasso_weights = process_weights_group_lasso(groups=groups,
+                                                        weights=lasso_weights)
+
             objective += lasso_pen * \
                 group_lasso_penalty(coef, groups=groups, weights=lasso_weights)
 
@@ -195,7 +199,7 @@ def setup_problem(X, y,
 
     # Add ridge
     if ridge_pen is not None:
-        if tikhonov:
+        if tikhonov is not None:
             objective += ridge_pen * \
                 tikhonov_penalty(coef, tikhonov=tikhonov)
 

ya_glm/cvxpy/penalty.py

@@ -21,7 +21,7 @@ def tikhonov_penalty(coef, tikhonov):
 
 def multi_task_lasso_penalty(coef, weights=None):
 
-    row_norms = cp.norm(coef, p='fro', axis=1)
+    row_norms = cp.norm(coef, axis=1)
 
     if weights:
         return weights.T @ row_norms
@@ -31,7 +31,7 @@ def multi_task_lasso_penalty(coef, weights=None):
 
 def group_lasso_penalty(coef, groups, weights=None):
 
-    group_norms = [cp.norm(coef[grp_idxs], p='fro') for grp_idxs in groups]
+    group_norms = [cp.norm(coef[grp_idxs]) for grp_idxs in groups]
 
     if weights is None:
         return cp.sum(group_norms)