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Posted to commits@madlib.apache.org by fm...@apache.org on 2018/04/23 21:57:50 UTC
[06/15] madlib-site git commit: jupyter notebooks for 1.14 release
http://git-wip-us.apache.org/repos/asf/madlib-site/blob/3f849b9e/community-artifacts/Random-forest-v1.ipynb
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+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Random forest\n",
+ "\n",
+ "Random forests build an ensemble of classifiers, each of which is a tree model constructed using bootstrapped samples from the input data. The results of these models are then combined to yield a single prediction, which, at the expense of some loss in interpretation, have been found to be highly accurate.\n",
+ "\n",
+ "Please also refer to the decision tree user documentation for information relevant to the implementation of random forests in MADlib."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 72,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "The sql extension is already loaded. To reload it, use:\n",
+ " %reload_ext sql\n"
+ ]
+ }
+ ],
+ "source": [
+ "%load_ext sql"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 73,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "u'Connected: gpadmin@madlib'"
+ ]
+ },
+ "execution_count": 73,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Greenplum Database 5.4.0 on GCP (demo machine)\n",
+ "%sql postgresql://gpadmin@35.184.253.255:5432/madlib\n",
+ " \n",
+ "# PostgreSQL local\n",
+ "#%sql postgresql://fmcquillan@localhost:5432/madlib\n",
+ "\n",
+ "# Greenplum Database 4.3.10.0\n",
+ "#%sql postgresql://gpdbchina@10.194.10.68:61000/madlib"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 75,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "1 rows affected.\n"
+ ]
+ },
+ {
+ "data": {
+ "text/html": [
+ "<table>\n",
+ " <tr>\n",
+ " <th>version</th>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>MADlib version: 1.14-dev, git revision: rc/1.13-rc1-40-ga1360f3, cmake configuration time: Wed Mar 28 18:16:08 UTC 2018, build type: release, build system: Linux-2.6.32-696.20.1.el6.x86_64, C compiler: gcc 4.4.7, C++ compiler: g++ 4.4.7</td>\n",
+ " </tr>\n",
+ "</table>"
+ ],
+ "text/plain": [
+ "[(u'MADlib version: 1.14-dev, git revision: rc/1.13-rc1-40-ga1360f3, cmake configuration time: Wed Mar 28 18:16:08 UTC 2018, build type: release, build system: Linux-2.6.32-696.20.1.el6.x86_64, C compiler: gcc 4.4.7, C++ compiler: g++ 4.4.7',)]"
+ ]
+ },
+ "execution_count": 75,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "%sql select madlib.version();\n",
+ "#%sql select version();"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Random forest classification examples"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# 1. Load data\n",
+ "Data set related to whether to play golf or not."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 76,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Done.\n",
+ "Done.\n",
+ "14 rows affected.\n",
+ "14 rows affected.\n"
+ ]
+ },
+ {
+ "data": {
+ "text/html": [
+ "<table>\n",
+ " <tr>\n",
+ " <th>id</th>\n",
+ " <th>OUTLOOK</th>\n",
+ " <th>temperature</th>\n",
+ " <th>humidity</th>\n",
+ " <th>Temp_Humidity</th>\n",
+ " <th>clouds_airquality</th>\n",
+ " <th>windy</th>\n",
+ " <th>class</th>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>1</td>\n",
+ " <td>sunny</td>\n",
+ " <td>85.0</td>\n",
+ " <td>85.0</td>\n",
+ " <td>[85.0, 85.0]</td>\n",
+ " <td>[u'none', u'unhealthy']</td>\n",
+ " <td>False</td>\n",
+ " <td>Don't Play</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>2</td>\n",
+ " <td>sunny</td>\n",
+ " <td>80.0</td>\n",
+ " <td>90.0</td>\n",
+ " <td>[80.0, 90.0]</td>\n",
+ " <td>[u'none', u'moderate']</td>\n",
+ " <td>True</td>\n",
+ " <td>Don't Play</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>3</td>\n",
+ " <td>overcast</td>\n",
+ " <td>83.0</td>\n",
+ " <td>78.0</td>\n",
+ " <td>[83.0, 78.0]</td>\n",
+ " <td>[u'low', u'moderate']</td>\n",
+ " <td>False</td>\n",
+ " <td>Play</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>4</td>\n",
+ " <td>rain</td>\n",
+ " <td>70.0</td>\n",
+ " <td>96.0</td>\n",
+ " <td>[70.0, 96.0]</td>\n",
+ " <td>[u'low', u'moderate']</td>\n",
+ " <td>False</td>\n",
+ " <td>Play</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>5</td>\n",
+ " <td>rain</td>\n",
+ " <td>68.0</td>\n",
+ " <td>80.0</td>\n",
+ " <td>[68.0, 80.0]</td>\n",
+ " <td>[u'medium', u'good']</td>\n",
+ " <td>False</td>\n",
+ " <td>Play</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>6</td>\n",
+ " <td>rain</td>\n",
+ " <td>65.0</td>\n",
+ " <td>70.0</td>\n",
+ " <td>[65.0, 70.0]</td>\n",
+ " <td>[u'low', u'unhealthy']</td>\n",
+ " <td>True</td>\n",
+ " <td>Don't Play</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>7</td>\n",
+ " <td>overcast</td>\n",
+ " <td>64.0</td>\n",
+ " <td>65.0</td>\n",
+ " <td>[64.0, 65.0]</td>\n",
+ " <td>[u'medium', u'moderate']</td>\n",
+ " <td>True</td>\n",
+ " <td>Play</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>8</td>\n",
+ " <td>sunny</td>\n",
+ " <td>72.0</td>\n",
+ " <td>95.0</td>\n",
+ " <td>[72.0, 95.0]</td>\n",
+ " <td>[u'high', u'unhealthy']</td>\n",
+ " <td>False</td>\n",
+ " <td>Don't Play</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>9</td>\n",
+ " <td>sunny</td>\n",
+ " <td>69.0</td>\n",
+ " <td>70.0</td>\n",
+ " <td>[69.0, 70.0]</td>\n",
+ " <td>[u'high', u'good']</td>\n",
+ " <td>False</td>\n",
+ " <td>Play</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>10</td>\n",
+ " <td>rain</td>\n",
+ " <td>75.0</td>\n",
+ " <td>80.0</td>\n",
+ " <td>[75.0, 80.0]</td>\n",
+ " <td>[u'medium', u'good']</td>\n",
+ " <td>False</td>\n",
+ " <td>Play</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>11</td>\n",
+ " <td>sunny</td>\n",
+ " <td>75.0</td>\n",
+ " <td>70.0</td>\n",
+ " <td>[75.0, 70.0]</td>\n",
+ " <td>[u'none', u'good']</td>\n",
+ " <td>True</td>\n",
+ " <td>Play</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>12</td>\n",
+ " <td>overcast</td>\n",
+ " <td>72.0</td>\n",
+ " <td>90.0</td>\n",
+ " <td>[72.0, 90.0]</td>\n",
+ " <td>[u'medium', u'moderate']</td>\n",
+ " <td>True</td>\n",
+ " <td>Play</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>13</td>\n",
+ " <td>overcast</td>\n",
+ " <td>81.0</td>\n",
+ " <td>75.0</td>\n",
+ " <td>[81.0, 75.0]</td>\n",
+ " <td>[u'medium', u'moderate']</td>\n",
+ " <td>False</td>\n",
+ " <td>Play</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>14</td>\n",
+ " <td>rain</td>\n",
+ " <td>71.0</td>\n",
+ " <td>80.0</td>\n",
+ " <td>[71.0, 80.0]</td>\n",
+ " <td>[u'low', u'unhealthy']</td>\n",
+ " <td>True</td>\n",
+ " <td>Don't Play</td>\n",
+ " </tr>\n",
+ "</table>"
+ ],
+ "text/plain": [
+ "[(1, u'sunny', 85.0, 85.0, [85.0, 85.0], [u'none', u'unhealthy'], False, u\"Don't Play\"),\n",
+ " (2, u'sunny', 80.0, 90.0, [80.0, 90.0], [u'none', u'moderate'], True, u\"Don't Play\"),\n",
+ " (3, u'overcast', 83.0, 78.0, [83.0, 78.0], [u'low', u'moderate'], False, u'Play'),\n",
+ " (4, u'rain', 70.0, 96.0, [70.0, 96.0], [u'low', u'moderate'], False, u'Play'),\n",
+ " (5, u'rain', 68.0, 80.0, [68.0, 80.0], [u'medium', u'good'], False, u'Play'),\n",
+ " (6, u'rain', 65.0, 70.0, [65.0, 70.0], [u'low', u'unhealthy'], True, u\"Don't Play\"),\n",
+ " (7, u'overcast', 64.0, 65.0, [64.0, 65.0], [u'medium', u'moderate'], True, u'Play'),\n",
+ " (8, u'sunny', 72.0, 95.0, [72.0, 95.0], [u'high', u'unhealthy'], False, u\"Don't Play\"),\n",
+ " (9, u'sunny', 69.0, 70.0, [69.0, 70.0], [u'high', u'good'], False, u'Play'),\n",
+ " (10, u'rain', 75.0, 80.0, [75.0, 80.0], [u'medium', u'good'], False, u'Play'),\n",
+ " (11, u'sunny', 75.0, 70.0, [75.0, 70.0], [u'none', u'good'], True, u'Play'),\n",
+ " (12, u'overcast', 72.0, 90.0, [72.0, 90.0], [u'medium', u'moderate'], True, u'Play'),\n",
+ " (13, u'overcast', 81.0, 75.0, [81.0, 75.0], [u'medium', u'moderate'], False, u'Play'),\n",
+ " (14, u'rain', 71.0, 80.0, [71.0, 80.0], [u'low', u'unhealthy'], True, u\"Don't Play\")]"
+ ]
+ },
+ "execution_count": 76,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "%%sql\n",
+ "DROP TABLE IF EXISTS rf_golf CASCADE;\n",
+ "\n",
+ "CREATE TABLE rf_golf (\n",
+ " id integer NOT NULL,\n",
+ " \"OUTLOOK\" text,\n",
+ " temperature double precision,\n",
+ " humidity double precision,\n",
+ " \"Temp_Humidity\" double precision[],\n",
+ " clouds_airquality text[],\n",
+ " windy boolean,\n",
+ " class text\n",
+ ");\n",
+ "\n",
+ "INSERT INTO rf_golf VALUES\n",
+ "(1,'sunny', 85, 85, ARRAY[85, 85],ARRAY['none', 'unhealthy'], 'false','Don''t Play'),\n",
+ "(2, 'sunny', 80, 90, ARRAY[80, 90], ARRAY['none', 'moderate'], 'true', 'Don''t Play'),\n",
+ "(3, 'overcast', 83, 78, ARRAY[83, 78], ARRAY['low', 'moderate'], 'false', 'Play'),\n",
+ "(4, 'rain', 70, 96, ARRAY[70, 96], ARRAY['low', 'moderate'], 'false', 'Play'),\n",
+ "(5, 'rain', 68, 80, ARRAY[68, 80], ARRAY['medium', 'good'], 'false', 'Play'),\n",
+ "(6, 'rain', 65, 70, ARRAY[65, 70], ARRAY['low', 'unhealthy'], 'true', 'Don''t Play'),\n",
+ "(7, 'overcast', 64, 65, ARRAY[64, 65], ARRAY['medium', 'moderate'], 'true', 'Play'),\n",
+ "(8, 'sunny', 72, 95, ARRAY[72, 95], ARRAY['high', 'unhealthy'], 'false', 'Don''t Play'),\n",
+ "(9, 'sunny', 69, 70, ARRAY[69, 70], ARRAY['high', 'good'], 'false', 'Play'),\n",
+ "(10, 'rain', 75, 80, ARRAY[75, 80], ARRAY['medium', 'good'], 'false', 'Play'),\n",
+ "(11, 'sunny', 75, 70, ARRAY[75, 70], ARRAY['none', 'good'], 'true', 'Play'),\n",
+ "(12, 'overcast', 72, 90, ARRAY[72, 90], ARRAY['medium', 'moderate'], 'true', 'Play'),\n",
+ "(13, 'overcast', 81, 75, ARRAY[81, 75], ARRAY['medium', 'moderate'], 'false', 'Play'),\n",
+ "(14, 'rain', 71, 80, ARRAY[71, 80], ARRAY['low', 'unhealthy'], 'true', 'Don''t Play');\n",
+ "\n",
+ "SELECT * FROM rf_golf ORDER BY id;"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# 2. Train random forest\n",
+ "Train random forest then view the summary table:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 77,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Done.\n",
+ "1 rows affected.\n",
+ "1 rows affected.\n"
+ ]
+ },
+ {
+ "data": {
+ "text/html": [
+ "<table>\n",
+ " <tr>\n",
+ " <th>method</th>\n",
+ " <th>is_classification</th>\n",
+ " <th>source_table</th>\n",
+ " <th>model_table</th>\n",
+ " <th>id_col_name</th>\n",
+ " <th>dependent_varname</th>\n",
+ " <th>independent_varnames</th>\n",
+ " <th>cat_features</th>\n",
+ " <th>con_features</th>\n",
+ " <th>grouping_cols</th>\n",
+ " <th>num_trees</th>\n",
+ " <th>num_random_features</th>\n",
+ " <th>max_tree_depth</th>\n",
+ " <th>min_split</th>\n",
+ " <th>min_bucket</th>\n",
+ " <th>num_splits</th>\n",
+ " <th>verbose</th>\n",
+ " <th>importance</th>\n",
+ " <th>num_permutations</th>\n",
+ " <th>num_all_groups</th>\n",
+ " <th>num_failed_groups</th>\n",
+ " <th>total_rows_processed</th>\n",
+ " <th>total_rows_skipped</th>\n",
+ " <th>dependent_var_levels</th>\n",
+ " <th>dependent_var_type</th>\n",
+ " <th>independent_var_types</th>\n",
+ " <th>null_proxy</th>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>forest_train</td>\n",
+ " <td>True</td>\n",
+ " <td>rf_golf</td>\n",
+ " <td>train_output</td>\n",
+ " <td>id</td>\n",
+ " <td>class</td>\n",
+ " <td>\"OUTLOOK\",windy,temperature,humidity</td>\n",
+ " <td>\"OUTLOOK\",windy</td>\n",
+ " <td>temperature,humidity</td>\n",
+ " <td>None</td>\n",
+ " <td>20</td>\n",
+ " <td>2</td>\n",
+ " <td>8</td>\n",
+ " <td>3</td>\n",
+ " <td>1</td>\n",
+ " <td>10</td>\n",
+ " <td>False</td>\n",
+ " <td>True</td>\n",
+ " <td>1</td>\n",
+ " <td>1</td>\n",
+ " <td>0</td>\n",
+ " <td>14</td>\n",
+ " <td>0</td>\n",
+ " <td>\"Don't Play\",\"Play\"</td>\n",
+ " <td>text</td>\n",
+ " <td>text, boolean, double precision, double precision</td>\n",
+ " <td>None</td>\n",
+ " </tr>\n",
+ "</table>"
+ ],
+ "text/plain": [
+ "[(u'forest_train', True, u'rf_golf', u'train_output', u'id', u'class', u'\"OUTLOOK\",windy,temperature,humidity', u'\"OUTLOOK\",windy', u'temperature,humidity', None, 20, 2, 8, 3, 1, 10, False, True, 1, 1, 0, 14, 0, u'\"Don\\'t Play\",\"Play\"', u'text', u'text, boolean, double precision, double precision', u'None')]"
+ ]
+ },
+ "execution_count": 77,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "%%sql\n",
+ "DROP TABLE IF EXISTS train_output, train_output_group, train_output_summary;\n",
+ "\n",
+ "SELECT madlib.forest_train('rf_golf', -- source table\n",
+ " 'train_output', -- output model table\n",
+ " 'id', -- id column\n",
+ " 'class', -- response\n",
+ " '\"OUTLOOK\", temperature, humidity, windy', -- features\n",
+ " NULL, -- exclude columns\n",
+ " NULL, -- grouping columns\n",
+ " 20::integer, -- number of trees\n",
+ " 2::integer, -- number of random features\n",
+ " TRUE::boolean, -- variable importance\n",
+ " 1::integer, -- num_permutations\n",
+ " 8::integer, -- max depth\n",
+ " 3::integer, -- min split\n",
+ " 1::integer, -- min bucket\n",
+ " 10::integer -- number of splits per continuous variable\n",
+ " );\n",
+ "\n",
+ "SELECT * FROM train_output_summary;"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Review the group table for variable importance:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 78,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "1 rows affected.\n"
+ ]
+ },
+ {
+ "data": {
+ "text/html": [
+ "<table>\n",
+ " <tr>\n",
+ " <th>gid</th>\n",
+ " <th>success</th>\n",
+ " <th>cat_n_levels</th>\n",
+ " <th>cat_levels_in_text</th>\n",
+ " <th>oob_error</th>\n",
+ " <th>cat_var_importance</th>\n",
+ " <th>con_var_importance</th>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>1</td>\n",
+ " <td>True</td>\n",
+ " <td>[3, 2]</td>\n",
+ " <td>[u'overcast', u'sunny', u'rain', u'False', u'True']</td>\n",
+ " <td>0.57142857142857142857</td>\n",
+ " <td>[0.113988095238095, 0.0363095238095238]</td>\n",
+ " <td>[0.0, 0.0342261904761905]</td>\n",
+ " </tr>\n",
+ "</table>"
+ ],
+ "text/plain": [
+ "[(1, True, [3, 2], [u'overcast', u'sunny', u'rain', u'False', u'True'], Decimal('0.57142857142857142857'), [0.113988095238095, 0.0363095238095238], [0.0, 0.0342261904761905])]"
+ ]
+ },
+ "execution_count": 78,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "%%sql\n",
+ "SELECT * FROM train_output_group;"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "The 'cat_levels_in_text' array shows the ordering of the levels of the categorical variables \"OUTLOOK\" and windy, which have 3 and 2 levels respectively.\n",
+ "\n",
+ "Variable importance for categorical variables is shown in 'cat_var_importance'.\n",
+ "\n",
+ "Variable importance for continuous variables is shown in 'con_var_importance'.\n",
+ "\n",
+ "A higher value means higher importance for the variable."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "scrolled": true
+ },
+ "source": [
+ "# 3. Predict\n",
+ "Predict output categories. For the purpose of this example, we use the same data that was used for training:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 81,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Done.\n",
+ "1 rows affected.\n",
+ "14 rows affected.\n"
+ ]
+ },
+ {
+ "data": {
+ "text/html": [
+ "<table>\n",
+ " <tr>\n",
+ " <th>id</th>\n",
+ " <th>class</th>\n",
+ " <th>estimated_class</th>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>1</td>\n",
+ " <td>Don't Play</td>\n",
+ " <td>Don't Play</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>2</td>\n",
+ " <td>Don't Play</td>\n",
+ " <td>Don't Play</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>3</td>\n",
+ " <td>Play</td>\n",
+ " <td>Play</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>4</td>\n",
+ " <td>Play</td>\n",
+ " <td>Play</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>5</td>\n",
+ " <td>Play</td>\n",
+ " <td>Play</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>6</td>\n",
+ " <td>Don't Play</td>\n",
+ " <td>Don't Play</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>7</td>\n",
+ " <td>Play</td>\n",
+ " <td>Play</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>8</td>\n",
+ " <td>Don't Play</td>\n",
+ " <td>Don't Play</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>9</td>\n",
+ " <td>Play</td>\n",
+ " <td>Play</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>10</td>\n",
+ " <td>Play</td>\n",
+ " <td>Play</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>11</td>\n",
+ " <td>Play</td>\n",
+ " <td>Play</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>12</td>\n",
+ " <td>Play</td>\n",
+ " <td>Play</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>13</td>\n",
+ " <td>Play</td>\n",
+ " <td>Play</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>14</td>\n",
+ " <td>Don't Play</td>\n",
+ " <td>Don't Play</td>\n",
+ " </tr>\n",
+ "</table>"
+ ],
+ "text/plain": [
+ "[(1, u\"Don't Play\", u\"Don't Play\"),\n",
+ " (2, u\"Don't Play\", u\"Don't Play\"),\n",
+ " (3, u'Play', u'Play'),\n",
+ " (4, u'Play', u'Play'),\n",
+ " (5, u'Play', u'Play'),\n",
+ " (6, u\"Don't Play\", u\"Don't Play\"),\n",
+ " (7, u'Play', u'Play'),\n",
+ " (8, u\"Don't Play\", u\"Don't Play\"),\n",
+ " (9, u'Play', u'Play'),\n",
+ " (10, u'Play', u'Play'),\n",
+ " (11, u'Play', u'Play'),\n",
+ " (12, u'Play', u'Play'),\n",
+ " (13, u'Play', u'Play'),\n",
+ " (14, u\"Don't Play\", u\"Don't Play\")]"
+ ]
+ },
+ "execution_count": 81,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "%%sql\n",
+ "DROP TABLE IF EXISTS prediction_results;\n",
+ "\n",
+ "SELECT madlib.forest_predict('train_output', -- tree model \n",
+ " 'rf_golf', -- new data table\n",
+ " 'prediction_results', -- output table\n",
+ " 'response'); -- show response\n",
+ "\n",
+ "SELECT g.id, class, estimated_class FROM prediction_results p, \n",
+ "rf_golf g WHERE p.id = g.id ORDER BY g.id;"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "To display the probabilities associated with each value of the dependent variable, set the 'type' parameter to 'prob':"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 82,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Done.\n",
+ "1 rows affected.\n",
+ "14 rows affected.\n"
+ ]
+ },
+ {
+ "data": {
+ "text/html": [
+ "<table>\n",
+ " <tr>\n",
+ " <th>id</th>\n",
+ " <th>class</th>\n",
+ " <th>estimated_prob_Don't Play</th>\n",
+ " <th>estimated_prob_Play</th>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>1</td>\n",
+ " <td>Don't Play</td>\n",
+ " <td>0.9</td>\n",
+ " <td>0.1</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>2</td>\n",
+ " <td>Don't Play</td>\n",
+ " <td>0.7</td>\n",
+ " <td>0.3</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>3</td>\n",
+ " <td>Play</td>\n",
+ " <td>0.15</td>\n",
+ " <td>0.85</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>4</td>\n",
+ " <td>Play</td>\n",
+ " <td>0.45</td>\n",
+ " <td>0.55</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>5</td>\n",
+ " <td>Play</td>\n",
+ " <td>0.25</td>\n",
+ " <td>0.75</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>6</td>\n",
+ " <td>Don't Play</td>\n",
+ " <td>0.8</td>\n",
+ " <td>0.2</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>7</td>\n",
+ " <td>Play</td>\n",
+ " <td>0.25</td>\n",
+ " <td>0.75</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>8</td>\n",
+ " <td>Don't Play</td>\n",
+ " <td>0.9</td>\n",
+ " <td>0.1</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>9</td>\n",
+ " <td>Play</td>\n",
+ " <td>0.2</td>\n",
+ " <td>0.8</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>10</td>\n",
+ " <td>Play</td>\n",
+ " <td>0.25</td>\n",
+ " <td>0.75</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>11</td>\n",
+ " <td>Play</td>\n",
+ " <td>0.35</td>\n",
+ " <td>0.65</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>12</td>\n",
+ " <td>Play</td>\n",
+ " <td>0.3</td>\n",
+ " <td>0.7</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>13</td>\n",
+ " <td>Play</td>\n",
+ " <td>0.1</td>\n",
+ " <td>0.9</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>14</td>\n",
+ " <td>Don't Play</td>\n",
+ " <td>0.8</td>\n",
+ " <td>0.2</td>\n",
+ " </tr>\n",
+ "</table>"
+ ],
+ "text/plain": [
+ "[(1, u\"Don't Play\", 0.9, 0.1),\n",
+ " (2, u\"Don't Play\", 0.7, 0.3),\n",
+ " (3, u'Play', 0.15, 0.85),\n",
+ " (4, u'Play', 0.45, 0.55),\n",
+ " (5, u'Play', 0.25, 0.75),\n",
+ " (6, u\"Don't Play\", 0.8, 0.2),\n",
+ " (7, u'Play', 0.25, 0.75),\n",
+ " (8, u\"Don't Play\", 0.9, 0.1),\n",
+ " (9, u'Play', 0.2, 0.8),\n",
+ " (10, u'Play', 0.25, 0.75),\n",
+ " (11, u'Play', 0.35, 0.65),\n",
+ " (12, u'Play', 0.3, 0.7),\n",
+ " (13, u'Play', 0.1, 0.9),\n",
+ " (14, u\"Don't Play\", 0.8, 0.2)]"
+ ]
+ },
+ "execution_count": 82,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "%%sql\n",
+ "DROP TABLE IF EXISTS prediction_results;\n",
+ "\n",
+ "SELECT madlib.forest_predict('train_output', -- tree model \n",
+ " 'rf_golf', -- new data table\n",
+ " 'prediction_results', -- output table\n",
+ " 'prob'); -- show probability\n",
+ "\n",
+ "SELECT g.id, class, \"estimated_prob_Don't Play\", \"estimated_prob_Play\" \n",
+ "FROM prediction_results p, rf_golf g WHERE p.id = g.id ORDER BY g.id;"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# 4. View tree in text format\n",
+ "View a single tree within the forest identified by 'gid' and 'sample_id', out of the several that were created:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 84,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "1 rows affected.\n"
+ ]
+ },
+ {
+ "data": {
+ "text/html": [
+ "<table>\n",
+ " <tr>\n",
+ " <th>get_tree</th>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>-------------------------------------<br> - Each node represented by 'id' inside ().<br> - Each internal nodes has the split condition at the end, while each<br> leaf node has a * at the end.<br> - For each internal node (i), its child nodes are indented by 1 level<br> with ids (2i+1) for True node and (2i+2) for False node.<br> - Number of (weighted) rows for each response variable inside [].'<br> The response label order is given as ['\"Don\\'t Play\"', '\"Play\"'].<br> For each leaf, the prediction is given after the '-->'<br> <br>-------------------------------------<br>(0)[4 4] \"OUTLOOK\" in {overcast}<br> (1)[0 3] * --> \"Play\"<br> (2)[4 1] humidity <= 80<br> (5)[1 1] * --> \"Don't Play\"<br> (6)[3 0] * --> \"Don't Play\"<br></td>\n",
+ " </tr>\n",
+ "</table>"
+ ],
+ "text/plain": [
+ "[(u'-------------------------------------\\n - Each node represented by \\'id\\' inside ().\\n - Each internal nodes has the split condition at the end, while each\\n leaf node has a * at the end.\\n - For each internal node (i), its child nodes are indented by 1 level\\n with ids (2i+1) for True node and (2i+2) for False node.\\n - Number of (weighted) rows for each response variable inside [].\\'\\n The response label order is given as [\\'\"Don\\\\\\'t Play\"\\', \\'\"Play\"\\'].\\n For each leaf, the prediction is given after the \\'-->\\'\\n \\n-------------------------------------\\n(0)[4 4] \"OUTLOOK\" in {overcast}\\n (1)[0 3] * --> \"Play\"\\n (2)[4 1] humidity <= 80\\n (5)[1 1] * --> \"Don\\'t Play\"\\n (6)[3 0] * --> \"Don\\'t Play\"\\n',)]"
+ ]
+ },
+ "execution_count": 84,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "%%sql\n",
+ "SELECT madlib.get_tree('train_output',1,7, FALSE);"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Please see the decision tree user docs for an explanation on how to interpret the tree display above."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# 5. View tree in dot format"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 85,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "1 rows affected.\n"
+ ]
+ },
+ {
+ "data": {
+ "text/html": [
+ "<table>\n",
+ " <tr>\n",
+ " <th>get_tree</th>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>digraph \"Classification tree for rf_golf\" {<br>\"0\" [label=\"\\\"OUTLOOK\\\" <= overcast\", shape=ellipse];<br>\"0\" -> \"1\"[label=\"yes\"];<br>\"1\" [label=\"\\\"Play\\\"\",shape=box];<br>\"0\" -> \"2\"[label=\"no\"];<br>\"2\" [label=\"humidity <= 80\", shape=ellipse];<br>\"2\" -> \"5\"[label=\"yes\"];<br>\"5\" [label=\"\\\"Don't Play\\\"\",shape=box];<br>\"2\" -> \"6\"[label=\"no\"];<br>\"6\" [label=\"\\\"Don't Play\\\"\",shape=box];<br><br>} //---end of digraph--------- </td>\n",
+ " </tr>\n",
+ "</table>"
+ ],
+ "text/plain": [
+ "[(u'digraph \"Classification tree for rf_golf\" {\\n\"0\" [label=\"\\\\\"OUTLOOK\\\\\" <= overcast\", shape=ellipse];\\n\"0\" -> \"1\"[label=\"yes\"];\\n\"1\" [label=\"\\\\\"Play\\\\\"\",shape=box];\\n\"0\" -> \"2\"[label=\"no\"];\\n\"2\" [label=\"humidity <= 80\", shape=ellipse];\\n\"2\" -> \"5\"[label=\"yes\"];\\n\"5\" [label=\"\\\\\"Don\\'t Play\\\\\"\",shape=box];\\n\"2\" -> \"6\"[label=\"no\"];\\n\"6\" [label=\"\\\\\"Don\\'t Play\\\\\"\",shape=box];\\n\\n} //---end of digraph--------- ',)]"
+ ]
+ },
+ "execution_count": 85,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "%%sql\n",
+ "SELECT madlib.get_tree('train_output',1,7);"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# 6. View tree in dot format with additional information"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 86,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "1 rows affected.\n"
+ ]
+ },
+ {
+ "data": {
+ "text/html": [
+ "<table>\n",
+ " <tr>\n",
+ " <th>get_tree</th>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <td>digraph \"Classification tree for rf_golf\" {<br>\"0\" [label=\"\\\"OUTLOOK\\\" <= overcast\\n impurity = 0.5\\n samples = 8\\n value = [4 4]\\n class = \\\"Don't Play\\\"\", shape=ellipse];<br>\"0\" -> \"1\"[label=\"yes\"];<br>\"1\" [label=\"\\\"Play\\\"\\n impurity = 0\\n samples = 3\\n value = [0 3]\",shape=box];<br>\"0\" -> \"2\"[label=\"no\"];<br>\"2\" [label=\"humidity <= 80\\n impurity = 0.32\\n samples = 5\\n value = [4 1]\\n class = \\\"Don't Play\\\"\", shape=ellipse];<br>\"2\" -> \"5\"[label=\"yes\"];<br>\"5\" [label=\"\\\"Don't Play\\\"\\n impurity = 0.5\\n samples = 2\\n value = [1 1]\",shape=box];<br>\"2\" -> \"6\"[label=\"no\"];<br>\"6\" [label=\"\\\"Don't Play\\\"\\n impurity = 0\\n samples = 3\\n value = [3 0]\",shape=box];<br><br>} //---end of digraph--------- </td>\n",
+ " </tr>\n",
+ "</table>"
+ ],
+ "text/plain": [
+ "[(u'digraph \"Classification tree for rf_golf\" {\\n\"0\" [label=\"\\\\\"OUTLOOK\\\\\" <= overcast\\\\n impurity = 0.5\\\\n samples = 8\\\\n value = [4 4]\\\\n class = \\\\\"Don\\'t Play\\\\\"\", shape=ellipse];\\n\"0\" -> \"1\"[label=\"yes\"];\\n\"1\" [label=\"\\\\\"Play\\\\\"\\\\n impurity = 0\\\\n samples = 3\\\\n value = [0 3]\",shape=box];\\n\"0\" -> \"2\"[label=\"no\"];\\n\"2\" [label=\"humidity <= 80\\\\n impurity = 0.32\\\\n samples = 5\\\\n value = [4 1]\\\\n class = \\\\\"Don\\'t Play\\\\\"\", shape=ellipse];\\n\"2\" -> \"5\"[label=\"yes\"];\\n\"5\" [label=\"\\\\\"Don\\'t Play\\\\\"\\\\n impurity = 0.5\\\\n samples = 2\\\\n value = [1 1]\",shape=box];\\n\"2\" -> \"6\"[label=\"no\"];\\n\"6\" [label=\"\\\\\"Don\\'t Play\\\\\"\\\\n impurity = 0\\\\n samples = 3\\\\n value = [3 0]\",shape=box];\\n\\n} //---end of digraph--------- ',)]"
+ ]
+ },
+ "execution_count": 86,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "%%sql\n",
+ "SELECT madlib.get_tree('train_output',1,7, TRUE, TRUE);"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "You may wish to visualize the tree using pygraphviz or another program that can handle dot format:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 88,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "1 rows affected.\n",
+ "True\n"
+ ]
+ },
+ {
+ "data": {
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<TRUNCATED>