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Make notebook code match book examples more closely in chapter 2

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Aurélien Geron 2017-06-01 09:53:20 +02:00
parent c226f328d3
commit 88acd2b4b9
1 changed files with 17 additions and 8 deletions
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25
02_end_to_end_machine_learning_project.ipynb
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@ -1154,16 +1154,12 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 69, "execution_count": null,
"metadata": { "metadata": {
"collapsed": false, "collapsed": true
"deletable": true,
"editable": true
}, },
"outputs": [], "outputs": [],
"source": [ "source": [
"from sklearn.pipeline import FeatureUnion\n",
"\n",
"num_attribs = list(housing_num)\n", "num_attribs = list(housing_num)\n",
"cat_attribs = [\"ocean_proximity\"]\n", "cat_attribs = [\"ocean_proximity\"]\n",
"\n", "\n",
@ -1177,7 +1173,20 @@
"cat_pipeline = Pipeline([\n", "cat_pipeline = Pipeline([\n",
" ('selector', DataFrameSelector(cat_attribs)),\n", " ('selector', DataFrameSelector(cat_attribs)),\n",
" ('label_binarizer', LabelBinarizer()),\n", " ('label_binarizer', LabelBinarizer()),\n",
" ])\n", " ])"
]
},
{
"cell_type": "code",
"execution_count": 69,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"from sklearn.pipeline import FeatureUnion\n",
"\n", "\n",
"full_pipeline = FeatureUnion(transformer_list=[\n", "full_pipeline = FeatureUnion(transformer_list=[\n",
" (\"num_pipeline\", num_pipeline),\n", " (\"num_pipeline\", num_pipeline),\n",
@ -1219,7 +1228,7 @@
"editable": true "editable": true
}, },
"source": [ "source": [
"# Prepare the data for Machine Learning algorithms" "# Select and train a model "
] ]
}, },
{ {