denichen
diff --git a/‎.DS_Store‎
0 Bytes b/‎.DS_Store‎
0 Bytes
diff --git a/‎Kaggle/.DS_Store‎
0 Bytes b/‎Kaggle/.DS_Store‎
0 Bytes
diff --git a/‎Kaggle/Titanic/.DS_Store‎
6 KB b/‎Kaggle/Titanic/.DS_Store‎
6 KB
diff --git a/‎Kaggle/Titanic/Titanic_DecisionTree.ipynb‎
Lines changed: 6 additions & 4 deletions b/‎Kaggle/Titanic/Titanic_DecisionTree.ipynb‎
Lines changed: 6 additions & 4 deletions
diff --git a/‎Kaggle/Titanic/decisionTreeTitantic.dot‎
Lines changed: 10 additions & 9 deletions b/‎Kaggle/Titanic/decisionTreeTitantic.dot‎
Lines changed: 10 additions & 9 deletions
diff --git a/‎Kaggle/Titanic/decisionTreeTitantic.png‎
-75.1 KB b/‎Kaggle/Titanic/decisionTreeTitantic.png‎
-75.1 KB
@@ -267,24 +267,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 30,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "clf = tree.DecisionTreeClassifier(max_depth=2) \n",
-    "clf = clf.fit(df[['Sex', 'Age', 'Fare']], df[['Survived']]) \n",
+    "clf = clf.fit(df[['Sex', 'Age']], df[['Survived']]) \n",
     "tree.export_graphviz(clf,\n",
     "                     out_file=\"decisionTreeTitantic.dot\",\n",
-    "                     feature_names=['Sex', 'Age', 'Fare'],\n",
+    "                     feature_names=['Sex', 'Age'],\n",
     "                     class_names=['Dead', 'Alive'],\n",
+    "                     proportion = True,\n",
+    "                     rotate = True, \n",
     "                     filled = True)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 31,
    "metadata": {
     "collapsed": true
    },
 
@@ -1,16 +1,17 @@
 digraph Tree {
 node [shape=box, style="filled", color="black"] ;
-0 [label="Sex <= 0.5\ngini = 0.473\nsamples = 891\nvalue = [549, 342]\nclass = Dead", fillcolor="#e5813960"] ;
-1 [label="Fare <= 48.2\ngini = 0.383\nsamples = 314\nvalue = [81, 233]\nclass = Alive", fillcolor="#399de5a6"] ;
-0 -> 1 [labeldistance=2.5, labelangle=45, headlabel="True"] ;
-2 [label="gini = 0.447\nsamples = 225\nvalue = [76, 149]\nclass = Alive", fillcolor="#399de57d"] ;
+rankdir=LR ;
+0 [label="Sex <= 0.5\ngini = 0.473\nsamples = 100.0%\nvalue = [0.616, 0.384]\nclass = Dead", fillcolor="#e5813960"] ;
+1 [label="Age <= 32.25\ngini = 0.383\nsamples = 35.2%\nvalue = [0.258, 0.742]\nclass = Alive", fillcolor="#399de5a6"] ;
+0 -> 1 [labeldistance=2.5, labelangle=-45, headlabel="True"] ;
+2 [label="gini = 0.414\nsamples = 24.9%\nvalue = [0.293, 0.707]\nclass = Alive", fillcolor="#399de595"] ;
 1 -> 2 ;
-3 [label="gini = 0.106\nsamples = 89\nvalue = [5, 84]\nclass = Alive", fillcolor="#399de5f0"] ;
+3 [label="gini = 0.287\nsamples = 10.3%\nvalue = [0.174, 0.826]\nclass = Alive", fillcolor="#399de5c9"] ;
 1 -> 3 ;
-4 [label="Age <= 6.5\ngini = 0.306\nsamples = 577\nvalue = [468, 109]\nclass = Dead", fillcolor="#e58139c4"] ;
-0 -> 4 [labeldistance=2.5, labelangle=-45, headlabel="False"] ;
-5 [label="gini = 0.444\nsamples = 24\nvalue = [8, 16]\nclass = Alive", fillcolor="#399de57f"] ;
+4 [label="Age <= 6.5\ngini = 0.306\nsamples = 64.8%\nvalue = [0.811, 0.189]\nclass = Dead", fillcolor="#e58139c4"] ;
+0 -> 4 [labeldistance=2.5, labelangle=45, headlabel="False"] ;
+5 [label="gini = 0.444\nsamples = 2.7%\nvalue = [0.333, 0.667]\nclass = Alive", fillcolor="#399de57f"] ;
 4 -> 5 ;
-6 [label="gini = 0.28\nsamples = 553\nvalue = [460, 93]\nclass = Dead", fillcolor="#e58139cb"] ;
+6 [label="gini = 0.28\nsamples = 62.1%\nvalue = [0.832, 0.168]\nclass = Dead", fillcolor="#e58139cb"] ;
 4 -> 6 ;
 }