Bandit Feedback - Organic best of vs Bandit best of.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Bandit Feedback - Organic Best of vs Bandit Best of\n",
    "\n",
    "In this notebook we use the bandit signal for the first time, in the simplest possible way.  We compare how a recommender system that always makes the most popular organic product as a recommender with a recommender system that always makes the most popular bandit product.\n",
    "\n",
    "We see that there can be differences in behaviour."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import gym, recogym\n",
    "from recogym import env_1_args\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "%config InlineBackend.figure_format = 'retina'\n",
    "plt.rcParams['figure.figsize'] = [6, 3]\n",
    "\n",
    "ABTestNumberOfUsers=5000\n",
    "NumberOfProducts=10\n",
    "NumberOfSamples = 20\n",
    "env_1_args['phi_var']=0.0\n",
    "env_1_args['number_of_flips']=10\n",
    "env_1_args['sigma_mu_organic'] = 2\n",
    "env_1_args['sigma_omega']=0\n",
    "env_1_args['random_seed'] = 42\n",
    "env_1_args['num_products'] = NumberOfProducts\n",
    "env_1_args['K'] = 5\n",
    "env_1_args['number_of_flips'] = 3\n",
    "env = gym.make('reco-gym-v1')\n",
    "env.init_gym(env_1_args)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from recogym.agents import OrganicUserEventCounterAgent, organic_user_count_args\n",
    "from recogym import Configuration\n",
    "\n",
    "organic_counter_agent = OrganicUserEventCounterAgent(Configuration({\n",
    "            **organic_user_count_args,\n",
    "            **env_1_args,\n",
    "            'select_randomly': True,\n",
    "        }))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = env.generate_logs(ABTestNumberOfUsers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>a</th>\n",
       "      <th>c</th>\n",
       "      <th>ps</th>\n",
       "      <th>ps-a</th>\n",
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       "      <th>z</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>organic</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>[0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, ...</td>\n",
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       "      <td>bandit</td>\n",
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       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>[0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, ...</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bandit</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>[0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, ...</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bandit</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>organic</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1</td>\n",
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bandit</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>[0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, ...</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bandit</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>[0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, ...</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bandit</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>4.0</td>\n",
       "      <td>organic</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>1</td>\n",
       "      <td>6.0</td>\n",
       "      <td>organic</td>\n",
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      "text/plain": [
       "     a    c   ps                                               ps-a  t  u  \\\n",
       "0  NaN  NaN  NaN                                               None  0  0   \n",
       "1  3.0  0.0  0.1  [0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, ...  1  0   \n",
       "2  4.0  0.0  0.1  [0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, ...  2  0   \n",
       "3  5.0  0.0  0.1  [0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, ...  3  0   \n",
       "4  NaN  NaN  NaN                                               None  0  1   \n",
       "5  2.0  0.0  0.1  [0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, ...  1  1   \n",
       "6  8.0  0.0  0.1  [0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, ...  2  1   \n",
       "7  4.0  0.0  0.1  [0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, ...  3  1   \n",
       "8  NaN  NaN  NaN                                               None  4  1   \n",
       "9  NaN  NaN  NaN                                               None  5  1   \n",
       "\n",
       "     v        z  \n",
       "0  0.0  organic  \n",
       "1  NaN   bandit  \n",
       "2  NaN   bandit  \n",
       "3  NaN   bandit  \n",
       "4  1.0  organic  \n",
       "5  NaN   bandit  \n",
       "6  NaN   bandit  \n",
       "7  NaN   bandit  \n",
       "8  4.0  organic  \n",
       "9  6.0  organic  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here is the data the following columns are present:\n",
    "* **`t`**—_`Time`_. Currently, _`Time`_ reflects the order of _`Events`_ but it does **not** represent the notion of the time in a physical sense.\n",
    "* **`u`**—_`User`_.\n",
    "* **`z`**—_`Event Type`_. There are two types of _`Events`_: _Organic_ and _Bandit_.\n",
    "* **`v`**—_`View`_. The column shows which _`Product`_ was shown to a _`User`_ in an _Organic_ _`Event`_.\n",
    "* **`a`**—_`Action`_. Currently, _`Action`_ is a _`Product`_ that was provided to a _`User`_ during a _Bandit_ _`Event`_.\n",
    "* **`c`**—_`Click`_. This is a _Reward_ for an _`Action`_ provided by the _`Agent`_.\n",
    "* **`ps`**—Probability of selecting a particular _`Action`_.\n",
    "\n",
    "**Note #1:** _`Time`_, _`User`_, _`Views`_, and _`Actions`_ **all** them start with _`0`_.\n",
    "\n",
    "**Note #2:** For any _`User`_, _Organic_ _`Event`_ _**always**_ precedes a _Bandit_ _`Event`_."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Analysis\n",
    "Let's analyse these histograms:\n",
    "* _Actions per Product_\n",
    "* _Clicks per Product_\n",
    "* _Views per Product_."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x120b45c18>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 263,
       "width": 390
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_, ax = plt.subplots()\n",
    "ax.set_title('Histogram of Actions per Product')\n",
    "\n",
    "ax.hist(data[data['z'] == 'bandit']['a'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It is evident that all _`Actions`_ are _*evenly*_ distributed.\n",
    "That is an expected behaviour because *all* _`Actions`_ are randomly applied for all _Bandit_ _`Events`_.  This is not typical behaviour (usually actions are personalised not random) and we will relax this assumption later in the course."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Clicks:  [419. 346. 487. 337. 384. 507. 372. 384. 475. 503.]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11efeb940>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 263,
       "width": 377
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "clicks = np.zeros(NumberOfProducts)\n",
    "bandits = data[data['z'] == 'bandit']\n",
    "for product_id in range(NumberOfProducts):\n",
    "    actions = bandits[bandits['a'] == product_id]\n",
    "    clicks[product_id] = np.sum(actions[actions['c'] == 1]['c'])\n",
    "    \n",
    "print(\"Clicks: \", clicks)\n",
    "\n",
    "_, ax = plt.subplots()\n",
    "ax.set_title('Histogram of Clicks per Product')\n",
    "\n",
    "ax.bar(range(NumberOfProducts), clicks)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can estimate a click through rate for each recommendation by dividing the number of times we obtained a click by the number of impressions.  This produces the following \"bandit best of\":"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11f0892b0>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 277,
       "width": 400
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from scipy.stats.distributions import beta\n",
    "\n",
    "clicks = np.zeros(NumberOfProducts)\n",
    "impressions = np.zeros(NumberOfProducts)\n",
    "lower_errors = np.zeros(NumberOfProducts)\n",
    "upper_errors = np.zeros(NumberOfProducts)\n",
    "bandits = data[data['z'] == 'bandit']\n",
    "for product_id in range(NumberOfProducts):\n",
    "    actions = bandits[bandits['a'] == product_id]\n",
    "    clicks[product_id] = np.sum(actions[actions['c'] == 1]['c'])\n",
    "    impressions[product_id] = sum(actions['a']==product_id)\n",
    "\n",
    "    # Compute expected value according to a beta distribution\n",
    "    expected_value = beta.ppf(0.500, clicks[product_id] + 1, impressions[product_id] - clicks[product_id] + 1)\n",
    "    # Compute a confidence interval\n",
    "    lower_bound = beta.ppf(0.025, clicks[product_id] + 1, impressions[product_id] - clicks[product_id] + 1)\n",
    "    upper_bound = beta.ppf(0.975, clicks[product_id] + 1, impressions[product_id] - clicks[product_id] + 1)\n",
    "    # Save difference as error\n",
    "    lower_errors[product_id] = expected_value - lower_bound\n",
    "    upper_errors[product_id] = upper_bound - expected_value\n",
    "    \n",
    "\n",
    "_, ax = plt.subplots()\n",
    "ax.set_title('Click through rate (non personalised)')\n",
    "\n",
    "ax.errorbar(range(NumberOfProducts),\n",
    "            clicks/impressions,\n",
    "            yerr = (lower_errors, upper_errors),\n",
    "            fmt = 'o',\n",
    "            ecolor = 'darkred',\n",
    "            capsize = 4)\n",
    "\n",
    "plt.ylim([0,0.025])\n",
    "plt.xlabel('Item ID')\n",
    "plt.ylabel('Click-through rate')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The non-personalised click through rate can be uses as a non-personalised agent.  This will be our first likelihood based agent."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from collections import defaultdict\n",
    "\n",
    "from recogym.agents.abstract import Agent\n",
    "\n",
    "class GreedySingleActionAgent(Agent):\n",
    "    def __init__(self, preferred_action, config = Configuration({'num_products': 10})):\n",
    "        super(GreedySingleActionAgent, self).__init__(config)\n",
    "        self.preferred_action = preferred_action\n",
    "        \n",
    "    def act(self, observation, reward, done):\n",
    "        prob = np.zeros(self.config.num_products)\n",
    "        prob[self.preferred_action] = 1.\n",
    "        return {\n",
    "            **super().act(observation, reward, done),\n",
    "            **{\n",
    "                'a': self.preferred_action,\n",
    "                'ps': prob[self.preferred_action],\n",
    "                'ps-a': prob,\n",
    "            },\n",
    "        }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The Greedy-Bandit agent will always take action 5\n"
     ]
    }
   ],
   "source": [
    "# Initialise bandit\n",
    "top_ctr_item = np.argmax(clicks/impressions)\n",
    "print('The Greedy-Bandit agent will always take action {0}'.format(top_ctr_item))\n",
    "greedy_bandit = GreedySingleActionAgent(top_ctr_item, Configuration(env_1_args))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The ads that in a non-personalised sense attracts the most clicks is not in general the same as a product that is often viewed organically, to see this we can plot the organic views:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Views:  [11512.  4417.  1424.  8863. 25520. 13516.  3378.  9001.  4898. 23705.]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11f5eb8d0>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 263,
       "width": 390
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "organics = data[data['z'] == 'organic']\n",
    "\n",
    "views = np.zeros(NumberOfProducts)\n",
    "for product_id in range(NumberOfProducts):\n",
    "    views[product_id] = organics[organics['v'] == product_id].shape[0]\n",
    "\n",
    "print(\"Views: \", views)\n",
    "\n",
    "_, ax = plt.subplots()\n",
    "ax.set_title('Histogram of Views per Product')\n",
    "\n",
    "ax.bar(range(NumberOfProducts), views)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11fe906d8>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 277,
       "width": 400
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot number of organic views on x-axis and CTR on y-axis\n",
    "CTR = np.array(clicks)/np.array(impressions)\n",
    "\n",
    "\n",
    "_, ax = plt.subplots()\n",
    "ax.set_title('CTR for number of organic views')\n",
    "\n",
    "ax.scatter(views, CTR, marker = '.', label = 'CTR')\n",
    "\n",
    "z = np.polyfit(views, CTR, 1)\n",
    "p = np.poly1d(z)\n",
    "ax.plot(views, p(views), color = 'darkgreen', label = 'Trend')\n",
    "\n",
    "plt.xlabel('Number of organic views')\n",
    "plt.ylabel('Click-through rate')\n",
    "\n",
    "plt.gca().set_ylim([0.007,0.016])\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "While there may be a relationship between popular products and high click through rate it is certainly not guaranteed.  This fact underlies the need to use bandit feedback.  Here we will develop our final organic agent as an organic best of to hammer home this point."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The organic-best-of agent will always take action 4\n"
     ]
    }
   ],
   "source": [
    "# Initialise bandit\n",
    "top_viewed_item = np.argmax(views)\n",
    "print('The organic-best-of agent will always take action {0}'.format(top_viewed_item))\n",
    "greedy_organic = GreedySingleActionAgent(top_viewed_item, Configuration(env_1_args))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Starting A/B-testing at 2019-06-20 15:57:03.413166\n",
      "Finished A/B-testing at 2019-06-20 15:59:49.649804\n"
     ]
    }
   ],
   "source": [
    "from datetime import datetime\n",
    "from recogym.evaluate_agent import verify_agents, plot_verify_agents\n",
    "\n",
    "print('Starting A/B-testing at {0}'.format(datetime.now()))\n",
    "result = verify_agents(env,\n",
    "                       10000,\n",
    "                       {'Greedy-Bandit': greedy_bandit,\n",
    "                        'Greedy-Organic': greedy_organic})\n",
    "print('Finished A/B-testing at {0}'.format(datetime.now()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x104991b70>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 333,
       "width": 393
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plot_verify_agents(result)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "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"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}