add a note about regularization strength

Author: rasbt

Diff for: code/ch04/ch04.ipynb

@@ -2028,6 +2028,9 @@
     "from sklearn.linear_model import LogisticRegression\n",
     "\n",
     "lr = LogisticRegression(penalty='l1', C=1.0)\n",
+    "# Note that C=1.0 is the default. You can increase\n",
+    "# or decrease it to make the regulariztion effect\n",
+    "# stronger or weaker, respectively.\n",
     "lr.fit(X_train_std, y_train)\n",
     "print('Training accuracy:', lr.score(X_train_std, y_train))\n",
     "print('Test accuracy:', lr.score(X_test_std, y_test))"