Add safe dot product for sparse matrices

jjerphan · jjerphan · commit 22a620d480f8 · 2021-02-26T16:45:59.000+01:00
diff --git a/sklearn/linear_model/_logistic.py b/sklearn/linear_model/_logistic.py
@@ -233,7 +233,11 @@ def _logistic_grad_hess(w, X, y, alpha, sample_weight=None):
 
     def Hs(s):
         ret = np.empty_like(s)
-        ret[:n_features] = np.linalg.multi_dot([X.T, dX, s[:n_features]])
+        if sparse.issparse(X):
+            XTdX = safe_sparse_dot(X.T, dX)
+            ret[:n_features] = safe_sparse_dot(XTdX, s[:n_features])
+        else:
+            ret[:n_features] = np.linalg.multi_dot([X.T, dX, s[:n_features]])
         ret[:n_features] += alpha * s[:n_features]
 
         # For the fit intercept case.
