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Updated Decision_Tree_Image function by removing tree_ attribute from… #1

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Updated Decision_Tree_Image function by removing tree_ attribute from… #1

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60 changes: 18 additions & 42 deletions ...2_Supervised/ Correlation, supervised segmentation, and tree-structured models 2017.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -32,9 +32,7 @@
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [],
"source": [
"# Import the libraries we will be using\n",
Expand Down Expand Up @@ -73,9 +71,7 @@
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [],
"source": [
"\n",
Expand All @@ -84,7 +80,7 @@
"def Decision_Tree_Image(decision_tree, feature_names, name=\"temp\"):\n",
" \n",
" # Export our decision tree to graphviz format\n",
" dot_file = tree.export_graphviz(decision_tree.tree_, out_file='images/' + name + '.dot', feature_names=feature_names)\n",
" dot_file = tree.export_graphviz(decision_tree, out_file='images/' + name + '.dot', feature_names=feature_names)\n",
" \n",
" # Call graphviz to make an image file from our decision tree\n",
" os.system(\"dot -T png images/\" + name + \".dot -o images/\" + name + \".png\")\n",
Expand Down Expand Up @@ -156,9 +152,7 @@
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [],
"source": [
"# Set the randomness\n",
Expand Down Expand Up @@ -207,9 +201,7 @@
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [
{
"data": {
Expand Down Expand Up @@ -276,9 +268,7 @@
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [
{
"data": {
Expand Down Expand Up @@ -323,7 +313,6 @@
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [
Expand Down Expand Up @@ -392,9 +381,7 @@
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [],
"source": [
"\n",
Expand Down Expand Up @@ -440,9 +427,7 @@
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [
{
"name": "stdout",
Expand All @@ -469,7 +454,6 @@
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [
Expand Down Expand Up @@ -515,9 +499,7 @@
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [
{
"data": {
Expand All @@ -538,9 +520,7 @@
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [
{
"data": {
Expand Down Expand Up @@ -578,9 +558,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [],
"source": [
"Decision_Surface(X,Y,decision_tree)"
Expand All @@ -589,9 +567,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [],
"source": [
"print ( \"Accuracy = %.3f\" % (metrics.accuracy_score(decision_tree.predict(X), Y)) )"
Expand All @@ -609,23 +585,23 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 2",
"display_name": "Python 3",
"language": "python",
"name": "python2"
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.13"
"pygments_lexer": "ipython3",
"version": "3.6.1"
}
},
"nbformat": 4,
"nbformat_minor": 0
"nbformat_minor": 1
}