Binary Search Interactive (n_estimators).ipynb

{
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   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 1\n",
    "\n",
    "import pandas as pd\n",
    "import binarygridsearch.binarygridsearch as bgs\n",
    "%aimport binarygridsearch.binarygridsearch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import precision_recall_curve\n",
    "from sklearn.metrics import auc\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.model_selection import RandomizedSearchCV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Define a function that just returns accuracy\n",
    "def getForestAccuracy(X, y, kwargs):\n",
    "    clf = RandomForestClassifier(**kwargs)\n",
    "    clf.fit(X, y)\n",
    "    y_pred = clf.oob_decision_function_[:, 1]\n",
    "    precision, recall, _ = precision_recall_curve(y, y_pred)\n",
    "    return auc(recall, precision)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.datasets import load_breast_cancer\n",
    "data = load_breast_cancer()\n",
    "X, y = data.data, data.target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "rfArgs = {\"random_state\": 0,\n",
    "          \"n_jobs\": -1,\n",
    "          \"class_weight\": \"balanced\",\n",
    "         \"oob_score\": True}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "n_estimators = bgs.compareValsBaseCase(X, \n",
    "                    y, \n",
    "                    getForestAccuracy,        \n",
    "                    rfArgs, \n",
    "                    \"n_estimators\", \n",
    "                    0, \n",
    "                    32, \n",
    "                    128)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
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       "      <th></th>\n",
       "      <th>n_estimators</th>\n",
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      "text/plain": [
       "   n_estimators     score      time  scoreTimeRatio\n",
       "0            32  2.542509  0.003529        1.000000\n",
       "1           128  1.774372  1.003529        0.000000\n",
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       "      <th>1</th>\n",
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       "   n_estimators     score      time\n",
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",
      "text/plain": [
       "<VegaLite 2 object>\n",
       "\n",
       "If you see this message, it means the renderer has not been properly enabled\n",
       "for the frontend that you are using. For more information, see\n",
       "https://altair-viz.github.io/user_guide/troubleshooting.html\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bgs.showTimeScoreChartAndGraph(n_estimators)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "n_estimators = bgs.compareValsBaseCase(X, \n",
    "                    y, \n",
    "                    getForestAccuracy,        \n",
    "                    rfArgs, \n",
    "                    \"n_estimators\", \n",
    "                    0, \n",
    "                    68, \n",
    "                    80)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "   n_estimators      score      time  scoreTimeRatio\n",
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",
      "text/plain": [
       "<VegaLite 2 object>\n",
       "\n",
       "If you see this message, it means the renderer has not been properly enabled\n",
       "for the frontend that you are using. For more information, see\n",
       "https://altair-viz.github.io/user_guide/troubleshooting.html\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bgs.showTimeScoreChartAndGraph(n_estimators)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:py36]",
   "language": "python",
   "name": "conda-env-py36-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}