Fix sklearn.cross_decomposition.test_pls.test_scale_and_stability

sklearn/cross_decomposition/pls_.py

@@ -53,6 +53,11 @@ def _nipals_twoblocks_inner_loop(X, Y, mode="A", max_iter=500, tol=1e-06,
         else:  # mode A
             # Mode A regress each X column on y_score
             x_weights = np.dot(X.T, y_score) / np.dot(y_score.T, y_score)
+        # If y_score only has zeros x_weights will only have zeros. In
+        # this case add an epsilon to converge to a more acceptable
+        # solution
+        if np.dot(x_weights.T, x_weights) < eps:
+            x_weights += eps
         # 1.2 Normalize u
         x_weights /= np.sqrt(np.dot(x_weights.T, x_weights)) + eps
         # 1.3 Update x_score: the X latent scores