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Commit afd2b50c authored by Nikita Titov's avatar Nikita Titov Committed by Qiwei Ye
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[python] made notebook example interactive (#1791) 

* made notebook example interactive

* cleanup
parent f0e75fc1
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examples/python-guide/notebooks/interactive_plot_example.ipynb 0 → 100644
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Load libraries"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"ExecuteTime": {
"end_time": "2018-10-25T22:13:39.152526Z",
"start_time": "2018-10-25T22:13:37.503680Z"
},
"collapsed": true
},
"outputs": [],
"source": [
"import pandas as pd\n",
"import lightgbm as lgb\n",
"\n",
"import matplotlib.pyplot as plt\n",
"\n",
"%matplotlib inline\n",
"\n",
"try:\n",
" # To enable interactive mode you should install ipywidgets\n",
" # https://github.com/jupyter-widgets/ipywidgets\n",
" from ipywidgets import interact, SelectMultiple\n",
" INTERACTIVE = True\n",
"except ImportError:\n",
" INTERACTIVE = False"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Load data"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"ExecuteTime": {
"end_time": "2018-10-25T22:13:39.238695Z",
"start_time": "2018-10-25T22:13:39.160165Z"
},
"collapsed": true
},
"outputs": [],
"source": [
"df_train = pd.read_csv('../../regression/regression.train', header=None, sep='\\t')\n",
"df_test = pd.read_csv('../../regression/regression.test', header=None, sep='\\t')\n",
"\n",
"y_train = df_train[0]\n",
"y_test = df_test[0]\n",
"X_train = df_train.drop(0, axis=1)\n",
"X_test = df_test.drop(0, axis=1)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Create Dataset object for LightGBM"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"lgb_train = lgb.Dataset(X_train, y_train)\n",
"lgb_test = lgb.Dataset(X_test, y_test, reference=lgb_train)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Configuration dictionary"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"ExecuteTime": {
"end_time": "2018-10-25T22:13:39.243104Z",
"start_time": "2018-10-25T22:13:39.240578Z"
},
"collapsed": true
},
"outputs": [],
"source": [
"params = {\n",
" 'num_leaves': 5,\n",
" 'metric': ['l1', 'l2'],\n",
" 'verbose': -1\n",
"}"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Training"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"ExecuteTime": {
"end_time": "2018-10-25T22:13:39.336630Z",
"start_time": "2018-10-25T22:13:39.246006Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[10]\ttraining's l1: 0.457448\ttraining's l2: 0.217995\tvalid_1's l1: 0.456464\tvalid_1's l2: 0.21641\n",
"[20]\ttraining's l1: 0.436869\ttraining's l2: 0.205099\tvalid_1's l1: 0.434057\tvalid_1's l2: 0.201616\n",
"[30]\ttraining's l1: 0.421302\ttraining's l2: 0.197421\tvalid_1's l1: 0.417019\tvalid_1's l2: 0.192514\n",
"[40]\ttraining's l1: 0.411107\ttraining's l2: 0.192856\tvalid_1's l1: 0.406303\tvalid_1's l2: 0.187258\n",
"[50]\ttraining's l1: 0.403695\ttraining's l2: 0.189593\tvalid_1's l1: 0.398997\tvalid_1's l2: 0.183688\n",
"[60]\ttraining's l1: 0.398704\ttraining's l2: 0.187043\tvalid_1's l1: 0.393977\tvalid_1's l2: 0.181009\n",
"[70]\ttraining's l1: 0.394876\ttraining's l2: 0.184982\tvalid_1's l1: 0.389805\tvalid_1's l2: 0.178803\n",
"[80]\ttraining's l1: 0.391147\ttraining's l2: 0.1828\tvalid_1's l1: 0.386476\tvalid_1's l2: 0.176799\n",
"[90]\ttraining's l1: 0.388101\ttraining's l2: 0.180817\tvalid_1's l1: 0.384404\tvalid_1's l2: 0.175775\n",
"[100]\ttraining's l1: 0.385174\ttraining's l2: 0.179171\tvalid_1's l1: 0.382929\tvalid_1's l2: 0.175321\n"
]
}
],
"source": [
"evals_result = {} # to record eval results for plotting\n",
"gbm = lgb.train(params,\n",
" lgb_train,\n",
" num_boost_round=100,\n",
" valid_sets=[lgb_train, lgb_test],\n",
" feature_name=['f' + str(i + 1) for i in range(X_train.shape[-1])],\n",
" categorical_feature=[21],\n",
" evals_result=evals_result,\n",
" verbose_eval=10)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Plot metrics recorded during training"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"ExecuteTime": {
"end_time": "2018-10-25T22:13:39.809203Z",
"start_time": "2018-10-25T22:13:39.338985Z"
},
"collapsed": true
},
"outputs": [],
"source": [
"def render_metric(metric_name):\n",
" ax = lgb.plot_metric(evals_result, metric=metric_name, figsize=(10, 5))\n",
" plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
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RqfP8/f1JTU31dBn1Vp26ZBXMfnbMeIUdhSWeLkVERETErepUiCv3DeZO8wHPfHLsQf5E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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x17523ffa710>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"if INTERACTIVE:\n",
" # create widget to switch between metrics\n",
" interact(render_metric, metric_name=params['metric'])\n",
"else:\n",
" render_metric(params['metric'][0])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Plot feature importances"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"ExecuteTime": {
"end_time": "2018-10-25T22:13:39.958548Z",
"start_time": "2018-10-25T22:13:39.811530Z"
},
"collapsed": true
},
"outputs": [],
"source": [
"def render_plot_importance(importance_type, max_features=10,\n",
" ignore_zero=True, precision=4):\n",
" ax = lgb.plot_importance(gbm, importance_type=importance_type,\n",
" max_num_features=max_features,\n",
" ignore_zero=ignore_zero, figsize=(12, 8),\n",
" precision=precision)\n",
" plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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8FtgpInbKzP8EJtWxLkmSJKlXqPWDXVZFxEDgR8C/RcTTVD5+XJIkSdqh1TpD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\nwUAtSZIklWCgliRJkkowUEu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"text/plain": [
"<matplotlib.figure.Figure at 0x17528ea73c8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"if INTERACTIVE:\n",
" # create widget for interactive feature importance plot\n",
" interact(render_plot_importance,\n",
" importance_type=['split', 'gain'],\n",
" max_features=(1, X_train.shape[-1]),\n",
" precision=(0, 10))\n",
"else:\n",
" render_plot_importance(importance_type='split')"
]
},
{
"cell_type": "markdown",
"metadata": {
"ExecuteTime": {
"end_time": "2018-10-25T22:13:40.027803Z",
"start_time": "2018-10-25T22:13:39.960713Z"
}
},
"source": [
"## Plot trees"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def render_tree(tree_index, show_info, precision=4):\n",
" show_info = None if 'None' in show_info else show_info\n",
" return lgb.create_tree_digraph(gbm, tree_index=tree_index,\n",
" show_info=show_info, precision=precision)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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c3aVLqoRNmzYBSUI8PuORJI9lJEEjMbrnnnsC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\n2oa4Np166qlA0kZ26NABgMWLFwO5Jc6ztVNxbf7Zz35W5v7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5WTXxfde2pPny5csL1jfI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SAAAg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2bg6ljeu1OjfPM6639b6q6bPBsmL+E69dHNcxz475eCj3OkojefvttwH4xS9+AaTq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\nAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x17528fa6898>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"if INTERACTIVE:\n",
" # create widget to switch between trees and control info in nodes\n",
" interact(render_tree,\n",
" tree_index=(0, gbm.num_trees() - 1),\n",
" show_info=SelectMultiple( # allow multiple values to be selected\n",
" options=['None',\n",
" 'split_gain',\n",
" 'internal_value',\n",
" 'internal_count',\n",
" 'leaf_count'],\n",
" value=['None']),\n",
" precision=(0, 10))\n",
" tree = None\n",
"else:\n",
" tree = render_tree(84, ['None'])\n",
"tree"
]
}
],
"metadata": {
"hide_input": false,
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.3"
},
"varInspector": {
"cols": {
"lenName": 16,
"lenType": 16,
"lenVar": 40
},
"kernels_config": {
"python": {
"delete_cmd_postfix": "",
"delete_cmd_prefix": "del ",
"library": "var_list.py",
"varRefreshCmd": "print(var_dic_list())"
},
"r": {
"delete_cmd_postfix": ") ",
"delete_cmd_prefix": "rm(",
"library": "var_list.r",
"varRefreshCmd": "cat(var_dic_list()) "
}
},
"types_to_exclude": [
"module",
"function",
"builtin_function_or_method",
"instance",
"_Feature"
],
"window_display": false
}
},
"nbformat": 4,
"nbformat_minor": 2
}
examples/python-guide/notebooks/plot_example.ipynb deleted 100644 → 0
View file @ f0e75fc1
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Load libraries"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"ExecuteTime": {
"end_time": "2018-10-25T22:13:39.152526Z",
"start_time": "2018-10-25T22:13:37.503680Z"
}
},
"outputs": [],
"source": [
"import warnings\n",
"warnings.filterwarnings('ignore') #suppress lgb userwarnings\n",
"\n",
"import lightgbm as lgb\n",
"import pandas as pd\n",
"import graphviz\n",
"\n",
"if lgb.compat.MATPLOTLIB_INSTALLED:\n",
" import matplotlib.pyplot as plt\n",
" %matplotlib inline\n",
"else:\n",
" raise ImportError('You need to install matplotlib to run this notebook.')"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"ExecuteTime": {
"end_time": "2018-10-25T22:13:39.158186Z",
"start_time": "2018-10-25T22:13:39.154477Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"lightgbm version: 2.2.1\n",
"pandas version: 0.23.3\n"
]
}
],
"source": [
"print('lightgbm version: ' + lgb.__version__)\n",
"print('pandas version: ' + pd.__version__)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Load data..."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"ExecuteTime": {
"end_time": "2018-10-25T22:13:39.238695Z",
"start_time": "2018-10-25T22:13:39.160165Z"
}
},
"outputs": [],
"source": [
"df_train = pd.read_csv('../../regression/regression.train', header=None, sep='\\t')\n",
"df_test = pd.read_csv('../../regression/regression.test', header=None, sep='\\t')\n",
"\n",
"y_train = df_train[0].values\n",
"y_test = df_test[0].values\n",
"X_train = df_train.drop(0, axis=1).values\n",
"X_test = df_test.drop(0, axis=1).values\n",
"\n",
"# create dataset for lightgbm\n",
"lgb_train = lgb.Dataset(X_train, y_train)\n",
"lgb_test = lgb.Dataset(X_test, y_test, reference=lgb_train)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Configuration"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"ExecuteTime": {
"end_time": "2018-10-25T22:13:39.243104Z",
"start_time": "2018-10-25T22:13:39.240578Z"
}
},
"outputs": [],
"source": [
"params = {\n",
" 'num_leaves': 5,\n",
" 'metric': ('l1', 'l2'),\n",
" 'verbose': 0\n",
"}"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Training"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"ExecuteTime": {
"end_time": "2018-10-25T22:13:39.336630Z",
"start_time": "2018-10-25T22:13:39.246006Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[10]\ttraining's l2: 0.217995\ttraining's l1: 0.457448\tvalid_1's l2: 0.21641\tvalid_1's l1: 0.456464\n",
"[20]\ttraining's l2: 0.205099\ttraining's l1: 0.436869\tvalid_1's l2: 0.201616\tvalid_1's l1: 0.434057\n",
"[30]\ttraining's l2: 0.197421\ttraining's l1: 0.421302\tvalid_1's l2: 0.192514\tvalid_1's l1: 0.417019\n",
"[40]\ttraining's l2: 0.192856\ttraining's l1: 0.411107\tvalid_1's l2: 0.187258\tvalid_1's l1: 0.406303\n",
"[50]\ttraining's l2: 0.189593\ttraining's l1: 0.403695\tvalid_1's l2: 0.183688\tvalid_1's l1: 0.398997\n",
"[60]\ttraining's l2: 0.187043\ttraining's l1: 0.398704\tvalid_1's l2: 0.181009\tvalid_1's l1: 0.393977\n",
"[70]\ttraining's l2: 0.184982\ttraining's l1: 0.394876\tvalid_1's l2: 0.178803\tvalid_1's l1: 0.389805\n",
"[80]\ttraining's l2: 0.1828\ttraining's l1: 0.391147\tvalid_1's l2: 0.176799\tvalid_1's l1: 0.386476\n",
"[90]\ttraining's l2: 0.180817\ttraining's l1: 0.388101\tvalid_1's l2: 0.175775\tvalid_1's l1: 0.384404\n",
"[100]\ttraining's l2: 0.179171\ttraining's l1: 0.385174\tvalid_1's l2: 0.175321\tvalid_1's l1: 0.382929\n"
]
}
],
"source": [
"# train\n",
"evals_result = {} # to record eval results for plotting\n",
"gbm = lgb.train(params,\n",
" lgb_train,\n",
" num_boost_round=100,\n",
" valid_sets=[lgb_train, lgb_test],\n",
" feature_name=['f' + str(i + 1) for i in range(28)],\n",
" categorical_feature=[21],\n",
" evals_result=evals_result,\n",
" verbose_eval=10)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"ExecuteTime": {
"end_time": "2018-10-25T22:13:39.809203Z",
"start_time": "2018-10-25T22:13:39.338985Z"
}
},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"ax = lgb.plot_metric(evals_result, metric='l1')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"ExecuteTime": {
"end_time": "2018-10-25T22:13:39.958548Z",
"start_time": "2018-10-25T22:13:39.811530Z"
}
},
"outputs": [
{
"data": {
"image/png": 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"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"ax = lgb.plot_importance(gbm, max_num_features=10)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"ExecuteTime": {
"end_time": "2018-10-25T22:13:40.027803Z",
"start_time": "2018-10-25T22:13:39.960713Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Plotting 84th tree with graphviz\n"
]
},
{
"data": {
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"</svg>\n"
],
"text/plain": [
"<graphviz.dot.Digraph at 0x117a7f208>"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"print('Plotting 84th tree with graphviz')\n",
"lgb.create_tree_digraph(gbm, tree_index=83, name='Tree84', precision=4)"
]
}
],
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},
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},
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}
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