examples/kaggle_otto_xgboost.ipynb

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    "## Understanding XGBoost Model on Otto Dataset\n",
    "\n",
    "This example is ``pandas-ml`` transration based on kaggle's \"Understanding XGBoost Model on Otto Dataset\". To run this Jupyter Notebook, you must download data to ``otto_data`` directory.\n",
    "\n",
    "https://github.com/dmlc/xgboost/blob/master/demo/kaggle-otto/understandingXGBoostModel.Rmd"
   ]
  },
  {
   "cell_type": "code",
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   "metadata": {
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   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import os\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "pd.set_option('display.max_rows', 8)\n",
    "pd.set_option('display.max_rows', 6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas_ml as pdml"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "scrolled": true
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   "source": [
    "train_df = pd.read_csv(os.path.join('otto_data', 'train.csv'), header=0, index_col=0)\n",
    "test_df = pd.read_csv(os.path.join('otto_data', 'test.csv'), header=0, index_col=0)\n",
    "\n",
    "# convert to pdml.ModelFrame\n",
    "train_df = pdml.ModelFrame(train_df, target='target')\n",
    "test_df = pdml.ModelFrame(test_df)\n",
    "train_df"
   ]
  },
  {
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       "       feat_1  feat_2  feat_3  feat_4  feat_5  feat_6  feat_7  feat_8  feat_9  \\\n",
       "id                                                                              \n",
       "1           1       0       0       0       0       0       0       0       0   \n",
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       "\n",
       "       feat_10   ...    feat_85  feat_86  feat_87  feat_88  feat_89  feat_90  \\\n",
       "id               ...                                                           \n",
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       "1            0        0        0       0  \n",
       "2            0        0        0       0  \n",
       "3            0        0        0       0  \n",
       "...        ...      ...      ...     ...  \n",
       "61876        0        0        0       8  \n",
       "61877        3       10        0       8  \n",
       "61878        0        2        0       8  \n",
       "\n",
       "[61878 rows x 94 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df['target'], classes = train_df['target'].factorize()\n",
    "train_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index([u'Class_1', u'Class_2', u'Class_3', u'Class_4', u'Class_5', u'Class_6',\n",
       "       u'Class_7', u'Class_8', u'Class_9'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "classes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "XGBClassifier(base_score=0.5, colsample_bytree=1, gamma=0, learning_rate=0.1,\n",
       "       max_delta_step=0, max_depth=3, min_child_weight=1, missing=None,\n",
       "       n_estimators=100, nthread=-1, objective='multi:softprob', seed=0,\n",
       "       silent=True, subsample=1)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xgc = train_df.xgboost.XGBClassifier(objective=\"multi:softprob\")\n",
    "xgc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-0.65640179, -0.65812877, -0.65056929])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df.cross_validation.cross_val_score(xgc, cv=3, scoring='log_loss')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "XGBClassifier(base_score=0.5, colsample_bytree=1, gamma=0, learning_rate=0.1,\n",
       "       max_delta_step=0, max_depth=3, min_child_weight=1, missing=None,\n",
       "       n_estimators=100, nthread=-1, objective='multi:softprob', seed=0,\n",
       "       silent=True, subsample=1)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df.fit(xgc, eval_metric='mlogloss')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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zqx96HCvz8arvx9c79FyszMerfjA/sjrZkfv27aOgoCB4tECA3NxcbrrpptI+RD870jfZ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\nViEiIklVslcBohe4j8h6Ubs5s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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10ae38950>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "fig, ax = plt.subplots(figsize=(7, 20))\n",
    "train_df.xgboost.plot_importance(ax=ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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