{ "cells": [ { "cell_type": "markdown", "id": "707b79e6", "metadata": {}, "source": [ "# Logged Bandit Data\n", "\n", "Often times we want to work with logged bandit data. Here we show how to use coba to... \n", "\n", "1. Generate logged bandit data\n", "2. Evaluate/Learn policies from logged bandit data\n", "4. Evaluate/Learn exploration from logged bandit data" ] }, { "cell_type": "code", "execution_count": 1, "id": "96f4b635-dc71-49e4-ab25-988883e4f2bd", "metadata": { "tags": [] }, "outputs": [], "source": [ "import matplotlib.pyplot as plt" ] }, { "cell_type": "markdown", "id": "9ddce504", "metadata": {}, "source": [ "## Generate logged bandit data\n", "\n", "Coba can generate logged bandit data in one of two ways: an environment filter or an experiment.\n", "\n", "### Generate via filter\n", "\n", "When generated via filter logged data is produced at request time using a logging policy (i.e., `RandomLearner` in the example below)." ] }, { "cell_type": "code", "execution_count": 17, "id": "a91c8b39", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[{'context': None,\n", " 'actions': [[0.10673861019313335], [0.27717866748571396]],\n", " 'rewards': DiscreteReward([[[0.10674], [0.27718]], [0.48749, 0.35408]]),\n", " 'action': [0.10673861019313335],\n", " 'reward': 0.48748829974177416,\n", " 'probability': 0.5}]" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import coba as cb\n", "\n", "envs = cb.Environments.from_linear_synthetic(1,n_actions=2,n_action_features=1,n_context_features=0)\n", "lrn = cb.RandomLearner()\n", "\n", "list(envs.logged(cb.RandomLearner())[0].read())" ] }, { "cell_type": "markdown", "id": "ae2be5a8", "metadata": {}, "source": [ "### Generate via Experiment\n", "\n", "The results of an Experiment can also be used to create logged bandit data." ] }, { "cell_type": "code", "execution_count": 15, "id": "d66c0ebf", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[{'action': [0.10674],\n", " 'actions': [[0.10674], [0.27718]],\n", " 'context': None,\n", " 'probability': 0.5,\n", " 'reward': 0.48749,\n", " 'rewards': DiscreteReward([[[0.10674], [0.27718]], [0.48749, 0.35408]])}]" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import coba as cb\n", "\n", "envs = cb.Environments.from_linear_synthetic(1,n_actions=2,n_action_features=1,n_context_features=0)\n", "lrn = cb.RandomLearner()\n", "result = cb.Experiment(envs,lrn,cb.SequentialCB(['context','actions','rewards','action','reward','probability'])).run(quiet=True)\n", "\n", "list(cb.Environments.from_result(result)[0].read())" ] }, { "cell_type": "markdown", "id": "b8fcd114-3a5b-440f-98c7-fd266fcf1de6", "metadata": {}, "source": [ "## Evaluate/Learn Policies From Logged Data\n", "\n", "A common task when working with logged bandit feedback is to estimate how well a new policy would perform in the logged environment.\n", "\n", "To perform off policy evaluation there are three common estimators used in the literature:\n", "\n", " 1. Inverse Propensity Score (IPS) -- a higher-variance lower-bias estimator\n", " 2. Direct Method (DM) -- a lower-variance higher-bias estimator\n", " 3. Doubly Robust (DR) -- a lower-variance lower-bias estimator\n", " \n", "We will evaluate all three of these methods against ground truth using 208 simulated datasets.\n" ] }, { "cell_type": "markdown", "id": "d1ed5689-d0e6-492b-85fa-0242a3a60734", "metadata": {}, "source": [ "### 1. Create our evaluation data\n", "\n", "To create our logged data we use a `MisguidedLearner`. This learner will behave very differently from the evaluation policies." ] }, { "cell_type": "code", "execution_count": 2, "id": "81c7c907-b95e-40ee-b49f-75659346ec6e", "metadata": { "tags": [] }, "outputs": [], "source": [ "envs1 = cb.Environments.from_feurer().where(n_actions=(None,100)).reservoir(4_000,strict=True).scale(scale='minmax')\n", "logs1 = envs1.logged(cb.MisguidedLearner(cb.VowpalEpsilonLearner(features=[1,'a','ax']),1,-1)).shuffle(n=20)" ] }, { "cell_type": "markdown", "id": "513a3563-463b-4e8b-9c9e-800ae5b376a6", "metadata": {}, "source": [ "### 2. Define the experiment" ] }, { "cell_type": "code", "execution_count": 3, "id": "42987398-7157-493e-b1df-13e944022d92", "metadata": { "tags": [] }, "outputs": [], "source": [ "evaluators = [ cb.SequentialCB(learn='off',eval=eval) for eval in ['on','ips','dr','dm']]\n", "experiment1 = cb.Experiment(logs1, cb.VowpalEpsilonLearner(features=[1,'a','ax']), evaluators )" ] }, { "cell_type": "markdown", "id": "c3257987-a5e5-43c9-bd59-62bff0907c5a", "metadata": {}, "source": [ "### 3. Run the experiment" ] }, { "cell_type": "code", "execution_count": 14, "id": "cf457718-257f-4899-ad32-bfd0ef482899", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: total: 40.6 s\n", "Wall time: 3h 3min 55s\n", "{'Learners': 1, 'Environments': 4940, 'Interactions': 37440000}\n" ] } ], "source": [ "%%time\n", "#WARNING: This can take some time to finish.\n", "#WARNING: To simply see the results look below.\n", "experiment1.run('out1.log.gz',processes=12,quiet=True)" ] }, { "cell_type": "markdown", "id": "f6b4ac2a-aa1f-418a-af9b-08e875909155", "metadata": {}, "source": [ "### 4. Analyze the results\n", "\n", "We plot the experimental results to see which one of our three options best utilized the logged data to predict online performance." ] }, { "cell_type": "code", "execution_count": 2, "id": "62d2e7c1-cfa3-4ea4-a04f-7038fbbdb895", "metadata": { "tags": [] }, "outputs": [], "source": [ "result1 = cb.Result.from_file('out1.log.gz')" ] }, { "cell_type": "code", "execution_count": 6, "id": "b1df0249-0198-468a-b8d3-0164e42ce982", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1.38\n", "9.182\n", "2.203\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "CPU times: total: 8.66 s\n", "Wall time: 18.8 s\n" ] } ], "source": [ "%%time\n", "result1.plot_learners(xlim=(200,None),l='eval',p=['openml_task','shuffle_seed'],labels=['DM','DR','IPS','GT'])" ] }, { "cell_type": "markdown", "id": "c439b50a-904e-4897-8adb-5cc306d068dd", "metadata": {}, "source": [ "In the plot above we can see how each of our reward estimators performed relative to the ground truth (GT). We know the ground truth due to working with simulated data. In practice, when working with real world data, we won't know this value and will have to use a reward estimator such as DM, DR, or IPS instead.\n", "\n", "Based on the plot above it appears that DM estimates GT most poorly while DR estimates it best. This is not the full story though because what is plotted above is the average over all of our data sets and so it can hide extreme errors. By hidden extremes what we mean is this, imagine two people are trying to estimate the height of a 5' tall person. We will call our two people estimators. The first estimator guesses the person is 3' tall and 7' tall while the second estimator guesses the person is 4'11\" and 5'1\" tall. Now both of these people were correct on average (i.e., for both estimators their average estimate was 5' which was the ground truth) but one of them we could argue was a better estimator because not only were they right on average but their estimates were also close to the ground truth. This is what we mean by hidden extremes. To look for this we create a contrast plot." ] }, { "cell_type": "code", "execution_count": 5, "id": "a0aed47f-d11b-46ed-a615-075ea40865c9", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "f,ax = plt.subplots(ncols=3,sharey=True,figsize=(10,4))\n", "\n", "result1.plot_contrast('on','ips',x='openml_task',l='eval',err='sd',ax=ax[0],xticks=False,legend=False,out=None)\n", "result1.plot_contrast('on','dm' ,x='openml_task',l='eval',err='sd',ax=ax[1],xticks=False,legend=False,out=None)\n", "result1.plot_contrast('on','dr' ,x='openml_task',l='eval',err='sd',ax=ax[2],xticks=False,legend=False,out=None)\n", "\n", "for a,title in zip(ax,['IPS$-$GT','DM$-$GT','DR$-$GT']):\n", " a.set_title('',loc='left')\n", " a.set_title(title,loc='center')\n", " a.set_xticks([])\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "7b90f829-d044-4787-b008-6af7f94a0927", "metadata": {}, "source": [ "The plot above shows the difference between the IPS, DM, and DR estimator relative to GT on all of our datasets. This is the distribution of estimates that are being averaged over in the the first plot. Here we can see that the DR estimator has a very similar pattern to the DM estimator but with smaller extremes. More specifically, the DR error ranges from approximately -0.1 to 0.2 while the DM error ranges from -0.2 to 0.3. We can show this same result as the variance of the mean." ] }, { "cell_type": "code", "execution_count": 7, "id": "8d1f0f22-1863-4a72-b4f7-85b86401f923", "metadata": {}, "outputs": [ { "data": { "image/png": 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HzZs3Y/PmzQgMDKz0wZi6MDIyQs+ePfHjjz9qPUoiJycHGzduROfOnSvcJVjXavq+11X5A0of/sdAWVlZhVPPTZs2hYuLS6WnY9PS0tCpU6darZ+IGhYeYdKzHTt2oLCwEAAwf/78CvPLLw5NTEys1VGA+fPnY9++fQgKCkJ0dDR8fHyQl5eHtLQ07NmzB3l5eZq+ISEh+Pjjj3HlyhWtYNSlSxesWrUK7u7uaNasmdb4L7/8Mv773/9CLpfDx8cHKSkp2LNnT4Vb3qvzwQcfYNeuXQgJCcG4ceNQWlqK5cuXo1WrVjh58qTo8h4eHvD19cWePXswevRoTfu0adOwY8cO9O3bF3l5efjmm2+0lhsxYoTm57feegsqlQpdunTBM888A6VSicTERJw/fx5LliyBlZUVrKys0L9//wrrLz+i9Oi8oKAgDBo0CDExMcjNzYWnpyc2bNiAS5cuYc2aNTq/Pjt37sT58+crtHfq1EnrQmtdmZiYYMCAAdi0aRNu376NxYsX13iMh3300UfYvXs3OnfujHHjxsHY2BirVq1CSUkJFi5c+Fhj11ZN3ve6CggIAAD85z//wZAhQ2BiYoKQkBB4eXnhtddeg5+fH6ysrLBnzx6cOHGiwrOhUlNTkZeXh379+ullG4monjPIvXmNWN++fau8dfzhycTEpMIt0uXKb42+fv16pfNzcnKE8ePHC66uroKJiYng5OQkdO/eXVi9erVWP5VKJRgZGQnW1tZat51/8803AgDh9ddfrzD2rVu3hFGjRgn29vaClZWVEBYWJpw/f1549tlntW7zFqtx//79QkBAgGBqaip4eHgICQkJNXrS99KlSwUrKyutxxx07dq12tf0Yd9++60QGhoqODo6CsbGxoKtra0QGhqq9QiFqlT1WAFBePBk7+nTpwtOTk6CTCYTOnToIOzatUunbarusQIAhHXr1gmCUPVr++ijAR62e/duAYAgkUiEK1euVLnuRx8rUNXfLy0tTQgLCxOsrKwECwsL4aWXXhKOHDmi1acmdVbVNzIyUrC0tKyw/sr+Brq872v62n344YfCM888I0ilUgGAkJmZKbz77ruCn5+fYG1tLVhaWgp+fn7CypUrK9Q4c+ZMwc3NTVCr1RVfQCJqdCSCoMNVkERPWEFBATw8PLBw4UKt02JE9UFJSQnc3d0xa9YsTJo0ydDlENETwGuYqF6Sy+WYMWMGFi1aVOndeUSGtG7dOpiYmFR43hMRNV48wkREREQkgkeYiIiIiEQwMBERERGJaJCBacWKFXB3d4eZmRmCgoJw/PjxKvueOXMGAwcOhLu7OyQSieaW8YfNnTsXEolEayp/eCIRERFRg3sO0+bNmzF16lQkJCQgKCgIy5YtQ1hYGDIzM9G0adMK/YuLi+Hh4YFBgwZhypQpVY7bqlUr7NmzR/O7sXHNXhq1Wo2srCxYW1vze6WIiIgaCEEQUFhYCBcXF0il1RxHMuhDDWohMDBQGD9+vOb3srIywcXFRYiPjxdd9tlnnxU++eSTCu2xsbGCn5/fY9V15coVnZ6/xIkTJ06cOHGqf1Nlz7B7WIM6wnTv3j2kpqYiJiZG0yaVShEaGoqUlJTHGvuvv/6Ci4sLzMzMEBwcjPj4+ArfeP6wkpISra9KEP7/zYZXrlx54l8dQURERLWjUqng6upa6Ze9P6xBBaYbN26grKwMjo6OWu2Ojo6VftWEroKCgrB+/Xp4eXkhOzsbH3zwAUJCQnD69OkqX8D4+Hh88MEHFdptbGwYmIiIiBoYsctpGuRF3/rWq1cvDBo0CG3atEFYWBh+/fVX5Ofn47vvvqtymZiYGBQUFGimK1euPMGKiYiI6ElqUEeY7O3tYWRkhJycHK32nJwcODk56W09CoUCzz//PC5evFhlH5lMBplMprd1EhERUf3VoI4wmZqaIiAgAElJSZo2tVqNpKQkBAcH6209RUVF+Pvvv+Hs7Ky3MYmIiKjhalBHmABg6tSpiIyMRPv27REYGIhly5bh9u3bGDVqFADgjTfewDPPPIP4+HgADy4UP3v2rObna9euISMjA1ZWVvD09AQATJ8+HX379sWzzz6LrKwsxMbGwsjICEOHDjXMRhIREVG90uACU0REBK5fv445c+ZAqVTC398fu3bt0lwIfvnyZa3nKGRlZaFt27aa3xcvXozFixeja9euSE5OBgBcvXoVQ4cOxc2bN+Hg4IDOnTvj6NGjcHBweKLbRkRERPUTv3xXT1QqFeRyOQoKCniXHBERUQOh6+d3g7qGiYiIiMgQGJiIiIiIRDAwERHp4MeMa4YugYgMiIGJiEgHP/2ZZegSiMiAGJiIiIiIRDAwEREREYlgYCIiIiISwcBEREREJIKBiYiIiEgEAxMRERGRCAYmIiIiIhEMTEREREQiGJiIiIiIRDAwEREREYlgYCIiIiISwcBEREREJIKBiYiIiEgEAxMRERGRCAYmIiIiIhEMTEREREQiGJiIiIiIRDAwEREREYlgYCIiIiISwcBEREREJIKBiYiIiEhEgwxMK1asgLu7O8zMzBAUFITjx49X2ffMmTMYOHAg3N3dIZFIsGzZsscek4iIiJ4uDS4wbd68GVOnTkVsbCzS0tLg5+eHsLAw5ObmVtq/uLgYHh4emD9/PpycnPQyJhERET1dGlxgWrp0KaKjozFq1Cj4+PggISEBFhYWWLt2baX9O3TogEWLFmHIkCGQyWR6GZOIiIieLg0qMN27dw+pqakIDQ3VtEmlUoSGhiIlJeWJjllSUgKVSqU1ERERUePUoALTjRs3UFZWBkdHR612R0dHKJXKJzpmfHw85HK5ZnJ1da3V+omIiKj+a1CBqT6JiYlBQUGBZrpy5YqhSyIiIqI6YmzoAmrC3t4eRkZGyMnJ0WrPycmp8oLuuhpTJpNVeU0UERERNS4N6giTqakpAgICkJSUpGlTq9VISkpCcHBwvRmTiIiIGpcGdYQJAKZOnYrIyEi0b98egYGBWLZsGW7fvo1Ro0YBAN544w0888wziI+PB/Dgou6zZ89qfr527RoyMjJgZWUFT09PncYkIiKip1uDC0wRERG4fv065syZA6VSCX9/f+zatUtz0fbly5chlf7fgbOsrCy0bdtW8/vixYuxePFidO3aFcnJyTqNSURERE83iSAIgqGLaAxUKhXkcjkKCgpgY2Nj6HKISM/e3HACX0V2MHQZRKRnun5+N6hrmIiIiIgMgYGJiIiISAQDExEREZEIBiYiIiIiEQxMRERERCIYmIiIiIhEMDA1AD9mXDN0CURERE81BqYG4Kc/swxdAhER0VONgYmIiIhIBAMTERERkQgGJiIiIiIRDExEREREIhiYiIiIqN4z9B3jDExERERU7xn6jnEGJiIiIiIRDExEREREIhiYiIiIiEQwMBERERGJYGAiIiIiEsHARERERCSCgYmIiIhIBAMTERERkQgGJiIiIiIRDExEREREIhiYiIiIiEQwMBERERGJaJCBacWKFXB3d4eZmRmCgoJw/Pjxavt///33aNmyJczMzNC6dWv8+uuvWvNHjhwJiUSiNYWHh9flJhAREVED0uAC0+bNmzF16lTExsYiLS0Nfn5+CAsLQ25ubqX9jxw5gqFDhyIqKgrp6eno378/+vfvj9OnT2v1Cw8PR3Z2tmb69ttvn8TmEBERUQPQ4ALT0qVLER0djVGjRsHHxwcJCQmwsLDA2rVrK+3/6aefIjw8HO+++y68vb3x4Ycfol27dvj888+1+slkMjg5OWkmW1vbausoKSmBSqXSmoiIiKhxalCB6d69e0hNTUVoaKimTSqVIjQ0FCkpKZUuk5KSotUfAMLCwir0T05ORtOmTeHl5YW3334bN2/erLaW+Ph4yOVyzeTq6lrLrSIiIqL6rkEFphs3bqCsrAyOjo5a7Y6OjlAqlZUuo1QqRfuHh4fj66+/RlJSEhYsWID9+/ejV69eKCsrq7KWmJgYFBQUaKYrV648xpYRERFRfWZs6ALqgyFDhmh+bt26Ndq0aYPnnnsOycnJ6N69e6XLyGQyyGSyJ1UiERERGVCDOsJkb28PIyMj5OTkaLXn5OTAycmp0mWcnJxq1B8APDw8YG9vj4sXLz5+0URERNTgNajAZGpqioCAACQlJWna1Go1kpKSEBwcXOkywcHBWv0BYPfu3VX2B4CrV6/i5s2bcHZ21k/hRERE1KA1qMAEAFOnTsWXX36JDRs24Ny5c3j77bdx+/ZtjBo1CgDwxhtvICYmRtN/0qRJ2LVrF5YsWYLz589j7ty5+OOPPzBhwgQAQFFREd59910cPXoUly5dQlJSEvr16wdPT0+EhYUZZBuJiIiofmlw1zBFRETg+vXrmDNnDpRKJfz9/bFr1y7Nhd2XL1+GVPp/ObBTp07YuHEjZs+ejffeew8tWrTADz/8AF9fXwCAkZERTp48iQ0bNiA/Px8uLi7o2bMnPvzwQ16jRERERAAaYGACgAkTJmiOED0qOTm5QtugQYMwaNCgSvubm5vjt99+02d5RERE1Mg0uFNyRERERE8aAxMRERGRCAYmIiIiIhEMTEREREQiGJiIiIiIRDAwEREREYlgYCIiIiISwcBEREREJIKBiYiIiEgEAxMRERGRCJ2/GmXq1Kk6D7p06dJaFUNERERUH+kcmNLT07V+T0tLQ2lpKby8vAAAFy5cgJGREQICAvRbIREREZGB6RyY9u3bp/l56dKlsLa2xoYNG2BrawsAuHXrFkaNGoWQkBD9V0lERERkQLW6hmnJkiWIj4/XhCUAsLW1xUcffYQlS5borTgiIiKi+qBWgUmlUuH69esV2q9fv47CwsLHLoqIiIioPqlVYHr11VcxatQobNu2DVevXsXVq1exdetWREVFYcCAAfqukYiIiMigdL6G6WEJCQmYPn06hg0bhvv37z8YyNgYUVFRWLRokV4LJCIiIjK0WgUmCwsLrFy5EosWLcLff/8NAHjuuedgaWmp1+KIiIiI6oMan5K7f/8+unfvjr/++guWlpZo06YN2rRpw7BEREREjVaNA5OJiQlOnjxZF7UQERER1Uu1uuh7xIgRWLNmjb5rISIiIqqXanUNU2lpKdauXYs9e/YgICCgwuk4fjUKERERNSa1CkynT59Gu3btADz4SpSHSSSSx6+KiIiIqB6pVWB6+GtSiIiIiBq7WgWmcmfPnsXly5dx7949TZtEIkHfvn0fuzAiIiKi+qJWF33/73//g5+fH3x9fdGnTx/0798f/fv3x6uvvor+/fvrucSKVqxYAXd3d5iZmSEoKAjHjx+vtv/333+Pli1bwszMDK1bt8avv/6qNV8QBMyZMwfOzs4wNzdHaGgo/vrrr7rcBCIiImpAahWYJk2ahObNmyM3NxcWFhY4c+YMDhw4gPbt2yM5OVnPJWrbvHkzpk6ditjYWKSlpcHPzw9hYWHIzc2ttP+RI0cwdOhQREVFIT09XRPuTp8+remzcOFCfPbZZ0hISMCxY8dgaWmJsLAw3L17t063hYiIiBoGiSAIQk0Xsre3x969e9GmTRvI5XIcP34cXl5e2Lt3L6ZNm4b09PS6qBUAEBQUhA4dOuDzzz8HAKjVari6umLixImYNWtWhf4RERG4ffs2fv75Z01bx44d4e/vj4SEBAiCABcXF0ybNg3Tp08HABQUFMDR0RHr16/HkCFDdKpLpVJBLpcjPz8fNjY2etjSB7IL7mDCxjR8PqwdnOXmehuXiGom+usT+PKNDoYug+ipVJefhSqVCgqFAgUFBdV+ftfqGqaysjJYW1sDeBCesrKy4OXlhWeffRaZmZm1q1gH9+7dQ2pqKmJiYjRtUqkUoaGhSElJqXSZlJQUTJ06VastLCwMP/zwAwDgn3/+gVKpRGhoqGa+XC5HUFAQUlJSqgxMJSUlKCkp0fyuUqkAAIWFhXq7U/D3s0p8vvciBAEYtjIZE7p5oqePk17GJqKasTVRo7Cw0NBlED116vqzUNf9ulan5Hx9ffHnn38CeHDEZ+HChTh8+DDi4uLg4eFRmyF1cuPGDZSVlcHR0VGr3dHREUqlstJllEpltf3L/1uTMQEgPj4ecrlcM7m6utZ4e6pzo6hE8wYBAEEAVuz9GzeKSqpfkIiIqJGoT5+FtTrCNHv2bNy+fRsAEBcXh5dffhkhISFo0qQJNm/erNcC66uYmBitI1cqlQqurq6wtrbWHH17HKdyS/Cv6tGzpQKUxRI0d3788YmoZm7dl+pl3yYi3T2Jz0Jdr0yqVWAKCwvT/Ozp6Ynz588jLy8Ptra2dfrgSnt7exgZGSEnJ0erPScnB05OlR+ec3JyqrZ/+X9zcnLg7Oys1cff37/KWmQyGWQyWYV2iUSil9fAw8EKEgmgfujvaCSRoLmDJR8OSmQQ+tm3iUh3T+KzUNdxanVK7o033sC6devw999/a9rs7Ozq/H8mpqamCAgIQFJSkqZNrVYjKSkJwcHBlS4THBys1R8Adu/erenfvHlzODk5afVRqVQ4duxYlWM+Cc5yc8QPaA2j//+aGkkkmDfAlxd+ExHRU6NefRYKtRAVFSW0aNFCkEgkQrNmzYThw4cLX375pXDhwoXaDFcjmzZtEmQymbB+/Xrh7NmzwpgxYwSFQiEolUpBEATh9ddfF2bNmqXpf/jwYcHY2FhYvHixcO7cOSE2NlYwMTERTp06pekzf/58QaFQCD/++KNw8uRJoV+/fkLz5s2FO3fu6FxXQUGBAEAoKCjQ38YKgpCVXyy8uuKQkJVfrNdxiahmotYfN3QJRE+tuvws1PXzu1an5L766isAwLVr13DgwAHs378fS5YswVtvvQVnZ2dcvXpVj5FOW0REBK5fv445c+ZAqVTC398fu3bt0ly0ffnyZUil/3fgrFOnTti4cSNmz56N9957Dy1atMAPP/wAX19fTZ8ZM2bg9u3bGDNmDPLz89G5c2fs2rULZmZmdbYdunKWm8PO0pRHloiI6KlVHz4LH+urUWxtbdGkSRPY2tpCoVDA2NgYDg4O+qqtShMmTMCECRMqnVfZgzMHDRqEQYMGVTmeRCJBXFwc4uLi9FUiERERNSK1uobpvffeQ6dOndCkSRPMmjULd+/exaxZs6BUKuv0oZVERIaQXXAHebfvIbvgjqFLISIDqdURpvnz58PBwQGxsbEYMGAAnn/+eX3XRURUL2w+cRkx205BLQAvzN+L+AGtEdHBzdBlEdETVqsjTOnp6fjPf/6D48eP44UXXsAzzzyDYcOGYfXq1bhw4YK+ayQiMojsgjuasAQ8uLX5vW2neaSJ6ClUq8Dk5+eHd955B9u2bcP169fx66+/wtTUFOPHj4e3t7e+ayQiMoh/btzWev4LAJQJAi7dKDZMQURkMLU6JScIAtLT05GcnIzk5GQcOnQIKpUKbdq0QdeuXfVdIxGRQTS3t4S0kofmudtbGK4oIjKIWgUmOzs7FBUVwc/PD127dkV0dDRCQkKgUCj0XB4RkeGUPzTvvW2nUSYIfIAs0VOsVoHpm2++QUhICGxsbPRdDxFRvRLRwQ1dnnfA+MQ0rBjejmGJ6ClVq8DUp08ffddBRFRv1YeH5hGRYdXqom8AOHjwIEaMGIHg4GBcu3YNAPDf//4Xhw4d0ltxRERERPVBrQLT1q1bERYWBnNzc6Snp6OkpAQAUFBQgHnz5um1QCIiIiJDq1Vg+uijj5CQkIAvv/wSJiYmmvYXXngBaWlpeiuOiIiIqD6oVWDKzMxEly5dKrTL5XLk5+c/bk1ERERE9UqtApOTkxMuXrxYof3QoUPw8PB47KKIiIiI6pNaBabo6GhMmjQJx44dg0QiQVZWFhITEzF9+nS8/fbb+q6RiIiIyKBq9ViBWbNmQa1Wo3v37iguLkaXLl0gk8kwffp0TJw4Ud81EhERERlUrQKTRCLBf/7zH7z77ru4ePEiioqK4OPjAysrK33XR0RERGRwNT4ld//+fXTv3h1//fUXTE1N4ePjg8DAQIYlIiIiarRqHJhMTExw8uTJuqiFiIiIqF6q1UXfI0aMwJo1a/RdCxEREVG9VKtrmEpLS7F27Vrs2bMHAQEBsLS01Jq/dOlSvRRHREREVB/UKjCdPn0a7dq1AwBcuHBBa55EInn8qoiIiIjqkVoFpn379um7DiIiIqJ6q1bXMBERERE9TRiYiIiIiEQwMBERERGJ0HtgOn36tL6HJCIiIjIovQSmwsJCrF69GkFBQfD399fHkJXKy8vD8OHDYWNjA4VCgaioKBQVFVW7zN27dzF+/Hg0adIEVlZWGDhwIHJycrT6SCSSCtOmTZvqbDuIiIioYXmswHTgwAFERkbC2dkZs2fPRrNmzSAIgr5qq2D48OE4c+YMdu/ejZ9//hkHDhzAmDFjql1mypQp+Omnn/D9999j//79yMrKwoABAyr0W7duHbKzszVT//7962griIiIqKGp8WMFlEol1q9fjzVr1iA7Oxv9+vXDd999h549e+L8+fP44Ycf6qBM4Ny5c9i1axdOnDiB9u3bAwCWL1+O3r17Y/HixXBxcamwTEFBAdasWYONGzeiW7duAB4EI29vbxw9ehQdO3bU9FUoFHByctK5npKSEpSUlGh+V6lUtd00IiIiqudqdISpb9++8PDwwMGDBzF37lzk5OQgMTERvXv3hrGxcZ0+tDIlJQUKhUITlgAgNDQUUqkUx44dq3SZ1NRU3L9/H6GhoZq2li1bws3NDSkpKVp9x48fD3t7ewQGBmLt2rWiR8ri4+Mhl8s1k6ur62NsHREREdVnNTrC9Msvv2DYsGGYPHmyVnB5EpRKJZo2barVZmxsDDs7OyiVyiqXMTU1hUKh0Gp3dHTUWiYuLg7dunWDhYUFfv/9d4wbNw5FRUV45513qqwnJiYGU6dO1fyuUqkYmoiIiBqpGh1hOnLkCMzNzdGtWzd4eXkhLi4Of//992MVMGvWrEovun54On/+/GOtQ8z777+PF154AW3btsXMmTMxY8YMLFq0qNplZDIZbGxstCYiIiJqnGoUmDp27Igvv/wS2dnZmDlzJn7//Xc8//zz6NixI5YvX17h7jNdTJs2DefOnat28vDwgJOTE3Jzc7WWLS0tRV5eXpXXHjk5OeHevXvIz8/Xas/Jyan2eqWgoCBcvXpV6xolIiIienrV6rvkLC0tMXr0aIwePRqZmZlYs2YN5s2bh5ycnBpfx+Tg4AAHBwfRfsHBwcjPz0dqaioCAgIAAHv37oVarUZQUFClywQEBMDExARJSUkYOHAgACAzMxOXL19GcHBwlevKyMiAra0tZDJZjbaFiIiIGqfHfg6Tl5cXFi5ciKtXr2Lbtm3o06ePPuqqwNvbG+Hh4YiOjsbx48dx+PBhTJgwAUOGDNHcIXft2jW0bNkSx48fBwDI5XJERUVh6tSp2LdvH1JTUzFq1CgEBwdr7pD76aef8NVXX+H06dO4ePEivvjiC8ybNw8TJ06sk+0gIiKihqdWR5gqY2RkhP79+9fp84sSExMxYcIEdO/eHVKpFAMHDsRnn32mmX///n1kZmaiuLhY0/bJJ59o+paUlCAsLAwrV67UzDcxMcGKFSswZcoUCIIAT09PLF26FNHR0XW2HURERNSw6C0wPQl2dnbYuHFjlfPd3d0rPA7AzMwMK1aswIoVKypdJjw8HOHh4Xqtk4iIiBoXfvkuERERkQgGJiIiIiIRDExEREREIhiYiIiIiEQwMBERERGJYGAiIiIiEsHARERERCSCgYmIiIhIBAMTERERkQgGJiIiIiIRDExEREREIhiYiIiIiEQwMBERERGJYGAiIiKieq+vn4tB18/ARERERPVeP/9nDLp+BiYiIiIiEQxMRERERCIYmIiIiIhEMDA1AIa+0I2IiOhpx8DUABj6QjciIqKnHQMTERERkQgGJiIiIiIRDExEREREIhiYiIiIiEQwMBERERGJaFCBKS8vD8OHD4eNjQ0UCgWioqJQVFRU7TKrV6/Giy++CBsbG0gkEuTn5+tlXCIiInp6NKjANHz4cJw5cwa7d+/Gzz//jAMHDmDMmDHVLlNcXIzw8HC89957eh2XiIiInh4SQRAEQxehi3PnzsHHxwcnTpxA+/btAQC7du1C7969cfXqVbi4VP9wx+TkZLz00ku4desWFAqF3sYtp1KpIJfLUVBQABsbm9ptJBHVW29uOIGvIjsYugwi0jNdP78bzBGmlJQUKBQKTagBgNDQUEilUhw7duyJj1tSUgKVSqU1ERERUePUYAKTUqlE06ZNtdqMjY1hZ2cHpVL5xMeNj4+HXC7XTK6urrWugYiIiOo3gwemWbNmQSKRVDudP3/e0GVWEBMTg4KCAs105coVQ5dEREREdcTY0AVMmzYNI0eOrLaPh4cHnJyckJubq9VeWlqKvLw8ODk51Xr9tR1XJpNBJpPVer1ERETUcBg8MDk4OMDBwUG0X3BwMPLz85GamoqAgAAAwN69e6FWqxEUFFTr9dfVuERERNR4GPyUnK68vb0RHh6O6OhoHD9+HIcPH8aECRMwZMgQzZ1s165dQ8uWLXH8+HHNckqlEhkZGbh48SIA4NSpU8jIyEBeXp7O4xIREdHTrcEEJgBITExEy5Yt0b17d/Tu3RudO3fG6tWrNfPv37+PzMxMFBcXa9oSEhLQtm1bREdHAwC6dOmCtm3bYseOHTqPS0RERE+3BvMcpvqOz2Eiatz4HCaixqnRPYeJiIiIyFAYmIiIiIhEMDARERERiWBgIiIiIhLBwEREREQkgoGJiIiISAQDExEREZEIBiYiIiIiEQxMRERERCIYmIiIiIhEMDARERERiWBgIiIiIhLBwEREREQkgoGJiIiISAQDExEREZEIBiYiIiIiEQxMRERERCIYmIiIiIhEMDARERERiWBgIiIiIhLBwEREREQkgoGJiIiISAQDExEREZEIBiYiIiIiEQxMRERERCIaVGDKy8vD8OHDYWNjA4VCgaioKBQVFVW7zOrVq/Hiiy/CxsYGEokE+fn5Ffq4u7tDIpFoTfPnz6+jrSAiIqKGpkEFpuHDh+PMmTPYvXs3fv75Zxw4cABjxoypdpni4mKEh4fjvffeq7ZfXFwcsrOzNdPEiRP1WToRERE1YMaGLkBX586dw65du3DixAm0b98eALB8+XL07t0bixcvhouLS6XLTZ48GQCQnJxc7fjW1tZwcnLSZ8lERETUSDSYI0wpKSlQKBSasAQAoaGhkEqlOHbs2GOPP3/+fDRp0gRt27bFokWLUFpaWm3/kpISqFQqrYmIiIgapwZzhEmpVKJp06ZabcbGxrCzs4NSqXyssd955x20a9cOdnZ2OHLkCGJiYpCdnY2lS5dWuUx8fDw++OCDx1ovERERNQwGP8I0a9asChdcPzqdP3++TmuYOnUqXnzxRbRp0wZjx47FkiVLsHz5cpSUlFS5TExMDAoKCjTTlStX6rRGIiIiMhyDH2GaNm0aRo4cWW0fDw8PODk5ITc3V6u9tLQUeXl5er/2KCgoCKWlpbh06RK8vLwq7SOTySCTyfS6XiIiIqqfDB6YHBwc4ODgINovODgY+fn5SE1NRUBAAABg7969UKvVCAoK0mtNGRkZkEqlFU4BEhER0dPJ4IFJV97e3ggPD0d0dDQSEhJw//59TJgwAUOGDNHcIXft2jV0794dX3/9NQIDAwE8uPZJqVTi4sWLAIBTp07B2toabm5usLOzQ0pKCo4dO4aXXnoJ1tbWSElJwZQpUzBixAjY2toabHuJiIio/jD4NUw1kZiYiJYtW6J79+7o3bs3OnfujNWrV2vm379/H5mZmSguLta0JSQkoG3btoiOjgYAdOnSBW3btsWOHTsAPDi1tmnTJnTt2hWtWrXCxx9/jClTpmiNS0RERE83iSAIgqGLaAxUKhXkcjkKCgpgY2Nj6HKISM/e3HACX0V2MHQZRKRnun5+N6gjTERERESGwMBEREREJIKBiYiIiEgEAxMRkQ76+lX+fZVE9HRgYCIi0kE//2cMXQIRGRADExEREZEIBiYiIiIiEQxMRERERCIYmIiIiIhEMDARERERiWBgIiIiIhLBwEREREQkgoGJiIiISISxoQtoLARBAPDgW4+JiIioYSj/3C7/HK8KA5OeFBYWAgBcXV0NXAkRERHVVGFhIeRyeZXzJYJYpCKdqNVqZGVlwdraGhKJRG/jqlQquLq64sqVK7CxsdHbuESkO+6HRIZVl/ugIAgoLCyEi4sLpNKqr1TiESY9kUqlaNasWZ2Nb2Njw/9RExkY90Miw6qrfbC6I0vleNE3ERERkQgGJiIiIiIRDEz1nEwmQ2xsLGQymaFLIXpqcT8kMqz6sA/yom8iIiIiETzCRERERCSCgYmIiIhIBAMTERERkQgGJiIiIiIRDEx6NnLkSPTv31/zs0QigUQigampKTw9PREXF4fS0lJN/y+//BJ+fn6wsrKCQqFA27ZtER8fr9O6tm7dim7dusHW1hbm5ubw8vLC6NGjkZ6ejuTkZM26q5qSk5Pr4BUgMqyH9zsTExM4OjqiR48eWLt2LdRqtaafu7s7JBIJNm3aVGGMVq1aQSKRYP369aLrU6lUeP/999GqVSuYm5ujSZMm6NChAxYuXIhbt25p1VPZ5O7ursetJ6ofarofSiQSWFhYoHXr1vjqq690Wse9e/ewaNEitGvXDpaWlpDL5fDz88Ps2bORlZWFuXPnin4O1gQDUx0LDw9HdnY2/vrrL0ybNg1z587FokWLAABr167F5MmT8c477yAjIwOHDx/GjBkzUFRUJDruzJkzERERAX9/f+zYsQOZmZnYuHEjPDw8EBMTg06dOiE7O1szDR48WFNL+dSpU6e63nwigyh/r1+6dAk7d+7ESy+9hEmTJuHll1/W+geLq6sr1q1bp7Xs0aNHoVQqYWlpKbqevLw8dOzYEevWrcP06dNx7NgxpKWl4eOPP0Z6ejo2btyITz/9VGu/A4B169Zpfj9x4oR+N56ontB1P4yLi0N2djZOnz6NESNGIDo6Gjt37qx27JKSEvTo0QPz5s3DyJEjceDAAZw6dQqfffYZbty4geXLl2P69Ola+16zZs0063p4f9SZQHoVGRkp9OvXr8LP5Xr06CF07NhREARB6NevnzBy5MgaryMlJUUAIHz66aeVzler1dXWRdSYVfVeT0pKEgAIX375pSAIgvDss88Ks2bNEmQymXD58mVNv+joaGHixImCXC4X1q1bV+263nrrLcHS0lK4du1apfMr2xcBCNu3b9d5e4gaoprsh5988olWHzs7O2HKlCnVjh8fHy9IpVIhLS2t0vmV7XuVrasmeITpCTM3N8e9e/cAAE5OTjh69Cj+/fffGo3x7bffwsrKCuPGjat0vj6//JeosejWrRv8/Pywbds2TZujoyPCwsKwYcMGAEBxcTE2b96M0aNHi46nVquxefNmjBgxAi4uLpX24b5IpK2y/bCcWq3G1q1bcevWLZiamlY7zrfffosePXqgbdu2lc6vi32PgekJEQQBe/bswW+//YZu3boBAGJjY6FQKODu7g4vLy+MHDkS3333ndb53cpcuHABHh4eMDb+v+9OXrp0KaysrDRTQUFBnW4PUUPUsmVLXLp0Satt9OjRWL9+PQRBwJYtW/Dcc8/B399fdKzr168jPz8fXl5eWu0BAQGa/XDo0KF6rJ6ocXh0P5w5cyasrKwgk8nw2muvwdbWFm+++Wa1Y1y4cKHCvvfqq69q9r26uOSEgamO/fzzz7CysoKZmRl69eqFiIgIzJ07FwDg7OyMlJQUnDp1CpMmTUJpaSkiIyMRHh4OtVqNgwcPaoWgxMTEKtczevRoZGRkYNWqVbh9+zYEPsCdqAJBECr8y7NPnz4oKirCgQMHsHbt2kqPLo0dO1ZrX6zO9u3bkZGRgbCwMNy5c0ev9RM1Bo/uh++++y4yMjKwd+9eBAUF4ZNPPoGnpycAYN68eVr73uXLl6scd+XKlcjIyMDo0aNRXFys97qNxbvQ43jppZfwxRdfwNTUFC4uLlpHhcr5+vrC19cX48aNw9ixYxESEoL9+/ejY8eOyMjI0PRzdHQEALRo0QKHDh3C/fv3YWJiAgBQKBRQKBS4evXqE9kuoobo3LlzaN68uVabsbExXn/9dcTGxuLYsWPYvn17heXi4uIwffp0rTYHBwcoFApkZmZqtbu5uQEArK2tkZ+fr98NIGoEHt0P7e3t4enpCU9PT3z//fdo3bo12rdvDx8fH4wdOxaDBw/W9C0//d2iRYsK+56zszMAwM7Ork7q5hGmOmZpaQlPT0+4ublVGpYe5ePjAwC4ffs2zM3NNW8iT09PWFtbAwCGDh2KoqIirFy5sk5rJ2pM9u7di1OnTmHgwIEV5o0ePRr79+9Hv379YGtrW2F+06ZNtfZFAJBKpRg8eDC++eYbZGVl1Xn9RI1Bdfsh8ODO1YiICMTExAB4EH4e3vfKP0eHDh2K3bt3Iz09/YnVziNMBvT222/DxcUF3bp1Q7NmzZCdnY2PPvoIDg4OCA4OrnK54OBgTJs2DdOmTcO///6LAQMGwNXVFdnZ2VizZg0kEgmkUmZhenqVlJRAqVSirKwMOTk52LVrF+Lj4/Hyyy/jjTfeqNDf29sbN27cgIWFRY3WM2/ePCQnJyMwMBBxcXFo3749LC0tcfLkSaSkpMDX11dfm0TU4NR0Pyw3adIk+Pr64o8//kD79u0r7TNlyhT88ssv6N69O2JjYxESEgJbW1tcuHABO3fuhJGRkd63h4HJgEJDQ7F27Vp88cUXuHnzJuzt7REcHIykpCQ0adKk2mUXL16MwMBAfPHFF1i7di2Ki4vh6OiILl26ICUlBTY2Nk9oK4jqn127dsHZ2RnGxsawtbWFn58fPvvsM0RGRlb5jwmxfa6qZY4fP44FCxZg0aJF+OeffyCVStGiRQtERERg8uTJj7klRA1XbfZD4MGZlp49e2LOnDn49ddfK+1jZmaGpKQkLFu2DOvWrUNMTAzUajWaN2+OXr16YcqUKXrfHonAq4OJiIiIqsXzNkREREQiGJiIiIiIRDAwEREREYlgYCIiIiISwcBEREREJIKBiYiIiEgEAxMRERGRCAYmIiIiIhEMTEREerZ+/XooFApDl0FEesTARERERCSCgYmIiIhIBAMTET111Go14uPj0bx5c5ibm8PPzw9btmyBWq1Gs2bN8MUXX2j1T09Ph1Qqxb///gsAWLp0KVq3bg1LS0u4urpi3LhxKCoqMsSmENETwsBERE+d+Ph4fP3110hISMCZM2cwZcoUjBgxAgcPHsTQoUOxceNGrf6JiYl44YUX8OyzzwIApFIpPvvsM5w5cwYbNmzA3r17MWPGDENsChE9IRJBEARDF0FE9KSUlJTAzs4Oe/bsQXBwsKb9zTffRHFxMWbMmIF27drh0qVLcHNzg1qthpubG2bPno2xY8dWOuaWLVswduxY3LhxA8CDi74nT56M/Pz8J7FJRPQEGBu6ACKiJ+nixYsoLi5Gjx49tNrv3buHtm3bwt/fH97e3ti4cSNmzZqF/fv3Izc3F4MGDdL03bNnD+Lj43H+/HmoVCqUlpbi7t27KC4uhoWFxZPeJCJ6AnhKjoieKuXXGv3yyy/IyMjQTGfPnsWWLVsAAMOHD9ecltu4cSPCw8PRpEkTAMClS5fw8ssvo02bNti6dStSU1OxYsUKAA9CFxE1TjzCRERPFR8fH8hkMly+fBldu3attM+wYcMwe/ZspKamYsuWLUhISNDMS01NhVqtxpIlSyCVPvg353ffffdEaiciw2FgIqKnirW1NaZPn44pU6ZArVajc+fOKCgowOHDh2FjY4PIyEi4u7ujU6dOiIqKQllZGV555RXN8p6enrh//z6WL1+Ovn374vDhw1qBiogaJ56SI6Knzocffoj3338f8fHx8Pb2Rnh4OH755Rc0b95c02f48OH4888/8eqrr8Lc3FzT7ufnh6VLl2LBggXw9fVFYmIi4uPjDbEZRPQE8S45IiIiIhE8wkREREQkgoGJiIiISAQDExEREZEIBiYiIiIiEQxMRERERCIYmIiIiIhEMDARERERiWBgIiIiIhLBwEREREQkgoGJiIiISAQDExEREZGI/wf66nEQOa8GiwAAAABJRU5ErkJggg==", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "result1.plot_contrast('on',['ips','dm','dr'],x='eval',l='eval',err='sd',boundary=False,legend=False,out=None)\n", "plt.axhline(0,color=\"#BBB\",alpha=.2)\n", "plt.xticks([0,1,2],['IPS-GT','DM-GT','DR-GT'])\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "45a7d7a6-a99c-410f-9244-d5d2cc93941a", "metadata": {}, "source": [ "The plot above shows a point estimate for difference from ground truth for each of our estimators at the 4,000th interaction. That is, each point in this plot is equal to the difference between each estimator and ground truth in the first figure. The blue lines shows standard deviation of the estimates making up each point. We can see that the standard deviation for the DM-GT errors is much larger than the standard deviation for IPS-GT error. This might seem counter-intuitive but it is a consequence of reporting the mean for all 4,000 rewards. We can see this more clearly below." ] }, { "cell_type": "code", "execution_count": 12, "id": "0a77876f-e6ca-4899-bbca-3f5a0f8be1aa", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(12,9))\n", "result1.plot_contrast('on','dm' ,x='index',l='eval',colors=0,err='sd',errevery=210,boundary=False,out=None,labels=['DM$-$GT' ])\n", "result1.plot_contrast('on','dr' ,x='index',l='eval',colors=1,err='sd',errevery=200,boundary=False,out=None,labels=['DR$-$GT' ])\n", "result1.plot_contrast('on','ips',x='index',l='eval',colors=2,err='sd',errevery=220,boundary=False,out=None,labels=['IPS$-$GT'])\n", "plt.legend(loc='lower left', bbox_to_anchor=(0,0))\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "ddb37eb7-5f08-41b4-af53-10bbe3fc8f07", "metadata": {}, "source": [ "The plot above shows the average difference between ground truth and DM/DR/IPS. We can see that while the variance of the DR/IPS estimators start out very large it eventually becomes smaller than DM around interaction 2,000 due to us averaging 2,000 observations. On the other hand the DM estimator stays consistent as the estimator is consistently right or wrong throughout all 4,000 interactions." ] }, { "cell_type": "markdown", "id": "98c9e199-ecb9-4fbc-bd98-88bbe89ebc39", "metadata": { "tags": [] }, "source": [ "---" ] }, { "cell_type": "markdown", "id": "12e31677-c2a3-4d74-a464-8d746d144f8e", "metadata": {}, "source": [ "## Evaluate/Learn Exploration From Logged Data\n", "\n", "Our goal is to use logged data to estimate online exploration performance.\n", "\n", "To do this we have three options:\n", " 1. Perform on-policy evaluation using a reward estimator\n", " 2. Perform off-policy evaluation using the logged data\n", " 3. Use rejection sampling to make the logged data look like the desired exploration\n", " \n", "We will evaluate all three options using logged data that we generate from a large set of classification datasets. By conducting this experiment over many datasets we can get a sense of the expected performance for each method independent of any one dataset. We will also intentionally use a misguided logging policy to generate our data to ensure that the logging policy doesn't look anything like the policies we wish to estimate. " ] }, { "cell_type": "markdown", "id": "728373ac-4396-42fd-a84c-22dbfc7932dc", "metadata": {}, "source": [ "### 1. Create evaluation data\n", "To create our logged data we use a `MisguidedLearner`. This learner behaves very differently from the policies we want to evaluate." ] }, { "cell_type": "code", "execution_count": 2, "id": "c9c40e31-8bcf-49f0-8dff-e20dd8da716f", "metadata": {}, "outputs": [], "source": [ "envs2 = cb.Environments.from_feurer().reservoir(30_000,strict=True).scale(scale='minmax')\n", "logs2 = envs2.logged(cb.MisguidedLearner(cb.VowpalEpsilonLearner(epsilon=.5,features=[1,'a','ax']),1,-1)).shuffle()" ] }, { "cell_type": "markdown", "id": "5eecd308-5d2b-4d9d-8d0d-528d74276cb7", "metadata": { "tags": [] }, "source": [ "### 2. Define the experiment " ] }, { "cell_type": "code", "execution_count": 3, "id": "5eac86f9-87bd-48ec-8f6a-3bcdfb975a57", "metadata": {}, "outputs": [], "source": [ "experiment2 = cb.Experiment(logs2, cb.VowpalEpsilonLearner(features=[1,'a','ax']), [\n", " cb.SequentialCB(learn='on' ,eval='on'), #GT\n", " cb.SequentialCB(learn='dr' ,eval='dr'), #on-policy learning from dr reward estimate (option 1)\n", " cb.SequentialCB(learn='off',eval='dr'), #off-policy learning (option 2)\n", " cb.RejectionCB () #rejection-sampling (option 3)\n", "])" ] }, { "cell_type": "markdown", "id": "f4cbb8ee-23b3-4dfd-9313-bccfc99945ae", "metadata": {}, "source": [ "### 3. Run the experiment" ] }, { "cell_type": "code", "execution_count": null, "id": "60fe9081-021b-4e28-b7c7-557544920b1f", "metadata": {}, "outputs": [], "source": [ "%%time\n", "#WARNING: This can take some time to finish.\n", "#WARNING: To simply see the results look below.\n", "experiment2.run('out2.log.gz',processes=4,quiet=True)" ] }, { "cell_type": "markdown", "id": "2b74da5d-c4b4-403f-b883-5217bf961e14", "metadata": {}, "source": [ "### 4. Analyze the results\n", "\n", "We plot the experimental results to see which one of our three options best utilized the logged data to predict online performance." ] }, { "cell_type": "code", "execution_count": 40, "id": "756b1741-9c53-41a1-b972-1f83b8579aca", "metadata": { "tags": [] }, "outputs": [], "source": [ "result2 = cb.Result.from_save('out2.log.gz')" ] }, { "cell_type": "code", "execution_count": 88, "id": "8a9244be-749d-4112-9ed0-fb64da355c30", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "labels=['third option','second option','first option','ground truth']\n", "result2.filter_fin(1000,l='evaluator_id',p='environment_id').plot_learners(xlim=(10,None),l='evaluator_id',p='environment_id',labels=['GT','On-Policy DR','Off-Policy','Rejection'])" ] }, { "cell_type": "markdown", "id": "707d4695-8752-45bc-969e-9f60ea924e23", "metadata": {}, "source": [ "In this plot the third option, rejection, looks pretty good. It almost perfectly matches the average online performance across 32 unique classification datasets. Unfortunately, this plot isn't the full story. To get this accuracy we had to sacrafice some data. Notice that the plot above only has 1,000 interactions but our original dataset had 30,000 examples.\n", "\n", "We now create a plot that shows the all 30,000 examples so we can see how much data was thrown out when using the `RejectionCB`." ] }, { "cell_type": "code", "execution_count": 84, "id": "84e0cf0f-29e2-43ad-a9df-de207f42dd2e", "metadata": { "tags": [] }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "eid = set(result2.filter_fin(1000).filter_fin(l='evaluator_id',p='openml_task').environments['environment_id'])\n", "\n", "result2\\\n", " .where(environment_id=eid)\\\n", " .where(eval_type={'!=':'RejectionCB'})\\\n", " .plot_learners(l='evaluator_id',p='openml_task',colors=[0,1,2],labels=['GT','On-Policy DR','Off-Policy'],out=None)\n", "\n", "result2\\\n", " .where(environment_id=eid)\\\n", " .where(eval_type={'=':'RejectionCB'})\\\n", " .filter_fin(1000,'evaluator_id','openml_task')\\\n", " .plot_learners(l='evaluator_id',p='openml_task',labels='Rejection',colors=3)" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.10.13" } }, "nbformat": 4, "nbformat_minor": 5 }