ch07 consistency fix

vnooli · Nov 16, 2019 · efb2e40 · efb2e40
1 parent b93da65
commit efb2e40
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Showing 2 changed files with 3 additions and 40 deletions.
diff --git a/ch07/ch07.ipynb b/ch07/ch07.ipynb
@@ -388,7 +388,7 @@
     "    classifiers : array-like, shape = [n_classifiers]\n",
     "      Different classifiers for the ensemble\n",
     "\n",
-    "    vote : str, {'classlabel', 'probability'} (default='label')\n",
+    "    vote : str, {'classlabel', 'probability'} (default='classlabel')\n",
     "      If 'classlabel' the prediction is based on the argmax of\n",
     "        class labels. Else if 'probability', the argmax of\n",
     "        the sum of probabilities is used to predict the class label\n",
@@ -924,43 +924,6 @@
    "source": [
     "from sklearn.model_selection import GridSearchCV\n",
     "\n",
-    "params = {'decisiontreeclassifier__max_depth': [1, 2],\n",
-    "          'pipeline-1__clf__C': [0.001, 0.1, 100.0]}\n",
-    "\n",
-    "grid = GridSearchCV(estimator=mv_clf,\n",
-    "                    param_grid=params,\n",
-    "                    cv=10,\n",
-    "                    iid=False,\n",
-    "                    scoring='roc_auc')\n",
-    "grid.fit(X_train, y_train)\n",
-    "\n",
-    "for r, _ in enumerate(grid.cv_results_['mean_test_score']):\n",
-    "    print(\"%0.3f +/- %0.2f %r\"\n",
-    "          % (grid.cv_results_['mean_test_score'][r], \n",
-    "             grid.cv_results_['std_test_score'][r] / 2.0, \n",
-    "             grid.cv_results_['params'][r]))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "0.944 +/- 0.07 {'decisiontreeclassifier__max_depth': 1, 'pipeline-1__clf__C': 0.001}\n",
-      "0.956 +/- 0.07 {'decisiontreeclassifier__max_depth': 1, 'pipeline-1__clf__C': 0.1}\n",
-      "0.978 +/- 0.03 {'decisiontreeclassifier__max_depth': 1, 'pipeline-1__clf__C': 100.0}\n",
-      "0.956 +/- 0.07 {'decisiontreeclassifier__max_depth': 2, 'pipeline-1__clf__C': 0.001}\n",
-      "0.956 +/- 0.07 {'decisiontreeclassifier__max_depth': 2, 'pipeline-1__clf__C': 0.1}\n",
-      "0.978 +/- 0.03 {'decisiontreeclassifier__max_depth': 2, 'pipeline-1__clf__C': 100.0}\n"
-     ]
-    }
-   ],
-   "source": [
-    "from sklearn.model_selection import GridSearchCV\n",
     "\n",
     "params = {'decisiontreeclassifier__max_depth': [1, 2],\n",
     "          'pipeline-1__clf__C': [0.001, 0.1, 100.0]}\n",
@@ -1717,5 +1680,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }
diff --git a/ch07/ch07.py b/ch07/ch07.py
@@ -164,7 +164,7 @@ class MajorityVoteClassifier(BaseEstimator,
     classifiers : array-like, shape = [n_classifiers]
       Different classifiers for the ensemble
 
-    vote : str, {'classlabel', 'probability'} (default='label')
+    vote : str, {'classlabel', 'probability'} (default='classlabel')
       If 'classlabel' the prediction is based on the argmax of
         class labels. Else if 'probability', the argmax of
         the sum of probabilities is used to predict the class label