chance-level-ap.ipynb

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   "source": [
    "import numpy as np\n",
    "from sklearn.metrics import average_precision_score\n",
    "\n",
    "def chance_level_ap(n_all, n_positive, trials=1000):\n",
    "    return np.mean([\n",
    "        average_precision_score([1] * n_positive + [0] * (n_all - n_positive), np.random.permutation(n_all))\n",
    "        for _ in range(trials)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
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   "source": [
    "import pytablewriter\n",
    "\n",
    "def create_table(config_pairs):\n",
    "    writer = pytablewriter.MarkdownTableWriter()\n",
    "    writer.header_list = ['Num of examples', 'True positive rate', 'Chance level AP']\n",
    "    writer.value_matrix = [\n",
    "        [n_all, positive_rate, chance_level_ap(n_all, round(n_all * positive_rate))]\n",
    "        for n_all, positive_rate in config_pairs\n",
    "    ]\n",
    "    return writer"
   ]
  },
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   "cell_type": "code",
   "execution_count": 3,
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     "name": "stderr",
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     "text": [
      "/Users/akiba/.pyenv/versions/anaconda3-4.2.0/lib/python3.5/site-packages/sklearn/metrics/ranking.py:444: RuntimeWarning: invalid value encountered in true_divide\n",
      "  recall = tps / tps[-1]\n"
     ]
    },
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       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>Num of examples</th>\n",
       "            <th>True positive rate</th>\n",
       "            <th>Chance level AP</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
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       "</table>\n"
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       "<pytablewriter.writer._markdown.MarkdownTableWriter at 0x1a086a26a0>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import itertools\n",
    "\n",
    "config_pairs = itertools.product([10, 100, 1000, 10000], [0.01, 0.1, 0.5, 0.9])\n",
    "\n",
    "create_table(config_pairs)"
   ]
  }
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