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{
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       "<style>\n",
       "    \n",
       "    @import url('http://fonts.googleapis.com/css?family=Source+Code+Pro');\n",
       "    \n",
       "    @import url('http://fonts.googleapis.com/css?family=Kameron');\n",
       "    @import url('http://fonts.googleapis.com/css?family=Crimson+Text');\n",
       "    \n",
       "    @import url('http://fonts.googleapis.com/css?family=Lato');\n",
       "    @import url('http://fonts.googleapis.com/css?family=Source+Sans+Pro');\n",
       "    \n",
       "    @import url('http://fonts.googleapis.com/css?family=Lora'); \n",
       "\n",
       "    \n",
       "    body {\n",
       "        font-family: 'Lora', Consolas, sans-serif;\n",
       "       \n",
       "        -webkit-print-color-adjust: exact important !;\n",
       "        \n",
       "      \n",
       "       \n",
       "    }\n",
       "    \n",
       "    .alert-block {\n",
       "        width: 95%;\n",
       "        margin: auto;\n",
       "    }\n",
       "    \n",
       "    .rendered_html code\n",
       "    {\n",
       "        color: black;\n",
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       "    div #notebook {\n",
       "        # font-size: 10pt; \n",
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       " \n",
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       "\n",
       "\n",
       "    }\n",
       "    \n",
       "    div#maintoolbar {display: none !important;}\n",
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       "</style>\n",
       "    <script>\n",
       "IPython.OutputArea.prototype._should_scroll = function(lines) {\n",
       "        return false;\n",
       "}\n",
       "    </script>\n"
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      "text/plain": [
       "<IPython.core.display.HTML object>"
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   ],
   "source": [
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    "# IGNORE THIS CELL WHICH CUSTOMIZES LAYOUT AND STYLING OF THE NOTEBOOK !\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "%config InlineBackend.figure_format = 'retina'\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore', category=FutureWarning)\n",
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    "warnings.filterwarnings('ignore', category=DeprecationWarning)\n",
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    "warnings.filterwarnings = lambda *a, **kw: None\n",
    "from IPython.core.display import HTML; HTML(open(\"custom.html\", \"r\").read())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Chapter 7: Regression\n",
    "\n",
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    "Regression belongs like classification to the field of supervised learning. \n",
    "\n",
    "<div class=\"alert alert-block alert-warning\">\n",
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    "<i class=\"fa fa-info-circle\"></i>&nbsp; \n",
    "<strong>Regression predicts numerical values</strong> \n",
    "in contrast to classification which predicts categories.\n",
    "</div>\n",
    "\n",
    "<img src=\"./images/30416v.jpg\" title=\"made at imgflip.com\" width=35%/>\n",
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    "\n",
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    "<div class=\"alert alert-block alert-warning\">\n",
    "<i class=\"fa fa-info-circle\"></i>&nbsp; \n",
    "    Other differences are:\n",
    "\n",
    "* Accuracy is measured differently\n",
    "\n",
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    "\n",
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    "* Other algorithms\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example: Salmon weight\n",
    "\n",
    "The dataset `data/salmon.csv` holds measurements of `circumference`, `length` and `weight` for  `atlantic` and `sockeye` salmons.\n",
    "\n",
    "Our goal is to predict `weight` based on the other three features."
   ]
  },
  {
   "cell_type": "code",
   "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",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>circumference</th>\n",
       "      <th>length</th>\n",
       "      <th>kind</th>\n",
       "      <th>weight</th>\n",
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