"
],
"text/plain": [
" ENGINESIZE CYLINDERS FUELCONSUMPTION_COMB CO2EMISSIONS\n",
"0 2.0 4 8.5 196\n",
"1 2.4 4 9.6 221\n",
"2 1.5 4 5.9 136\n",
"3 3.5 6 11.1 255\n",
"4 3.5 6 10.6 244\n",
"5 3.5 6 10.0 230\n",
"6 3.5 6 10.1 232\n",
"7 3.7 6 11.1 255\n",
"8 3.7 6 11.6 267"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cdf = df[['ENGINESIZE','CYLINDERS','FUELCONSUMPTION_COMB','CO2EMISSIONS']]\n",
"cdf.head(9)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can plot each of these features:\n"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"viz = cdf[['CYLINDERS','ENGINESIZE','CO2EMISSIONS','FUELCONSUMPTION_COMB']]\n",
"viz.hist()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now, let's plot each of these features against the Emission, to see how linear their relationship is:\n"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.scatter(cdf.FUELCONSUMPTION_COMB, cdf.CO2EMISSIONS, color='blue')\n",
"plt.xlabel(\"FUELCONSUMPTION_COMB\")\n",
"plt.ylabel(\"Emission\")\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.scatter(cdf.ENGINESIZE, cdf.CO2EMISSIONS, color='blue')\n",
"plt.xlabel(\"Engine size\")\n",
"plt.ylabel(\"Emission\")\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Practice\n",
"Plot __CYLINDER__ vs the Emission, to see how linear is their relationship is:\n"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.scatter(cdf.CYLINDERS, cdf.CO2EMISSIONS, color='blue')\n",
"plt.xlabel(\"Cylinders\")\n",
"plt.ylabel(\"Emission\")\n",
"plt.show()\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Click here for the solution\n",
"\n",
"```python \n",
"plt.scatter(cdf.CYLINDERS, cdf.CO2EMISSIONS, color='blue')\n",
"plt.xlabel(\"Cylinders\")\n",
"plt.ylabel(\"Emission\")\n",
"plt.show()\n",
"\n",
"```\n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Creating train and test dataset\n",
"Train/Test Split involves splitting the dataset into training and testing sets that are mutually exclusive. After which, you train with the training set and test with the testing set. \n",
"This will provide a more accurate evaluation on out-of-sample accuracy because the testing dataset is not part of the dataset that have been used to train the model. Therefore, it gives us a better understanding of how well our model generalizes on new data.\n",
"\n",
"This means that we know the outcome of each data point in the testing dataset, making it great to test with! Since this data has not been used to train the model, the model has no knowledge of the outcome of these data points. So, in essence, it is truly an out-of-sample testing.\n",
"\n",
"Let's split our dataset into train and test sets. 80% of the entire dataset will be used for training and 20% for testing. We create a mask to select random rows using __np.random.rand()__ function: \n"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [],
"source": [
"msk = np.random.rand(len(df)) < 0.8\n",
"train = cdf[msk]\n",
"test = cdf[~msk]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Simple Regression Model\n",
"Linear Regression fits a linear model with coefficients B = (B1, ..., Bn) to minimize the 'residual sum of squares' between the actual value y in the dataset, and the predicted value yhat using linear approximation. \n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Train data distribution\n"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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wc2bwMTNnmltvRwuDHSKKStFYffjrr0UQ4HSK+6+/Nr7vyOUSq1tvvCHu1b+iAz2ul2xzzR/9CCgv9/9ceTkDnrZq4UJgzpzWq5NOp3h84cLwzoeXscDLWETRKNqqD8fHAxcu6HtNoPdQWuq//9bEiSLI8X38hRf01esJ1HPKd9NvQ4MI2rScPs1LWm1VpFRQZrADBjtE0UpdFQG8Ax61+nCkFOUzEuh48tx3pL5n2f9z6/1eBGuuCXgHPBMmyG0Ezs8H1q3THkekF/fsEFHMi4bqw19/HVqgA7TsOwqWgRaInsw0Pc01AeCLL+TmIDuOyCoMdogoqhUUAIcPi9WPkhJxX1UVGYEOAFxxRejHUPcd7djRem+PDEUBqqvF64OZM0fueOq4tDS58bLjiKzSzu4JEBGFSq0+HInOnDH+WnXPzrBh4utQM8u0Xq+3uebkycBf/qI9fvJkueMSWYUrO0REFpLp3+SPv67noWaWab1eb3PN3r3lxsuOI7IKNyiDG5SJyDpffw307Kk9rls34LvvWr7OyRGBjuflOK0MtEBkM9P0NtcMZ/E4In+4QZmI2gyzastY4eKLgXYaGwbatROXmLT2HTmdIo0caFn5keW5QhSI3uaau3bJNXzctUt6mkSWYLBDRFEtGqoPnz8fOOBp1048L9v1PFAGWk6OCET8FXGbPVt+w7ae5pqxVMWaYhsvY4GXsYiiVaCaM5FWZ0f19dciO+vMGXH5Z/9+sfJjhG8vrX/+E7jzTvO+F2fPiqyrgwfFHp1Fi1pWdFSx1p+Mog+LCurAYIcossg0xVT3rwRKxY60CspWsut7EW1VrCn2cM8OEUUl2ctSWjVnZGvLxAK7vhfB9hD5yyYjsguDHSKKGHqaYsbafpFQNlnb+b0IZxXrpiYRPBUWivumJvOOTbGNRQWJKCIEa4WgKGKloKioZRNuNHY9DyRQY0/ZBp52fy8KCsTPRevSYyiKi4HFi72DwNmzgZkzw99Bm6IPV3aIKCLovRQzbJgICAKlYDscIkNJrT4cCfyt3uhZzQokGr8XehQXiw3SvqtdLpd4vLjYnnlR9GCwQ0QRQe+lmGjbL+JvL1LPnsAvfxl4NQuQa+Bp9/fCyvT/piaxohPM4sW8pEXBMdghoohg5FJMNHQ9B4Kv3hw/Hvh1ejYW2/W9MGNlKpjly+UKFy5fHtp5KLYx9RxMPSeKBKGkMcukqttFKy1cxhNPAJdfLvfewvm9CCXlXXaehYXAsmXac5k2DVi6VPdboCgn+/nNDcpEFBHUSzF33CE+JD0DHq1LMZHc9VxrL5KMefNa/q21cTmc3ws9+6w856RnQ3afPnJzkR1HbRMvYxFRxIiWy1J6mJ3ubdblITPIvrcPP2zZlP3WW/oue02Zor0y5XSKcUSB8DIWeBmLKNJE8mUpvWRbKugRKZWJjbw3pzPwHpxA70vNxgpkzhymn7dVbBehA4MdotgUCUFTXR3QqZP2uLg4oLlZ37GXLAEyMkJ7bzI9sAJxucT5g22yNsJfLy1/dXacTtbZaesY7OjAYIco9oRaqM8sEyZ4dwq3ipH3lp8PbNjQ+nHf7uaBWBXslJSI7u++mppE1tWhQ2KPzpQpQEKCueem6MJgRwcGO0SxJZK6oQ8cCFRWWn8eve8tUKCjkgl4rLhEB7BLOsljNhYRtUl6205YrU+f8AQ76nubPh1ISwOOHQt8eevs2eCBDiCe/+AD4MSJwMcxe/O1umcnWis9U+RisENEMcVoOrRVVq8GUlOtPw8g3ts33wCjR7c85u/y1pw5cse75ZbgxzGz11YkVr2m2MHUcyKKKVZ0ANfbkdyzO/crrwCDB8ufy2z+UroPHjTnOFo9uYLxDWiiubwART6u7BBRTDG7A7jejc6BsoYyMoCjR1uPj48HLlwIXDX6oouAVavEZamjR4EZM+TmrfLssaVeuuvXD9i8Wf9xfC8BqoUgb79d/jhqYPTGG0C3brFRXoAiHzcogxuUiWKJyyVSvRsaAo9JTQVOntT+cNW70VmrHkxhobiEpmYTrV4tgo477hDP+6sa7XkOrZYaWtSNv2fPAsnJ+l/vexxA+z136OD9s8jJEateXMEhMzAbSwcGO0Sxo6lJ1IkJVrMmLk584AdLW9bb96mpSQQQwS5xOZ3AmTOtz+tv9ShQUKAGYID+gOf114F77hH/1srGCkZNDZd9z++9J9LTuYJDZpP9/OaeHSKKKcuXaxfna27W7pKtZ6Ozel6j3bkLCoDDh8WKSUmJuK+q8r/6Eailhozvvmv59/r14nKUEeolQNn3/NlnIjgaMYKBDtmDe3aIKKbIbr7VGqd3o/OhQ3LjA43T08CzoEAEKmp16H37gPnztV/XrZv31+vXe1dQ7tMH2LgR+Pbb4J3n1dRws77XRFazdWVnxYoVGDhwIDp27IiOHTviuuuuw/vvv+9+/r777oPD4fC6XXvttV7HaGxsRGFhIbp27YqUlBSMHz8e34TaYpiIopZsZpDWOL0bncPdnVsNjiZOBG66Se41/laDkpKAZctETZ3ly4H//m/xuO/3x19quFnfayKr2RrsZGdn49lnn8Xu3buxe/du3HjjjcjLy8P+/fvdY2655RYcOXLEfXvvvfe8jlFUVIR169ZhzZo12LlzJxoaGjB27Fi4tNZWich2elO6ZY7ToYPca4YMCf68Vlq1wyH21airHHZ251bnGoznXIPR03n+mmvk5ic7jsgySoTp3Lmz8sorryiKoiiTJk1S8vLyAo49deqUEh8fr6xZs8b9WE1NjRIXF6ds2rQp4OvOnTun1NXVuW/V1dUKAKWurs6090FEwa1dqyjZ2YoiLpiIW3a2eDzU48jcliyRO3awY/jOdc6c4OPnzAl8rgsXFKWsTFFKSsT9hQv6vw8Oh//zOhz6v68y8ykrk/tel5XpOzeRrLq6OqnP74gJdi5cuKC88cYbSkJCgrJ//35FUUSwk5aWpnTr1k3p16+f8u///u/K0aNH3a/58MMPFQDKiRMnvI41cOBA5cknnwx4rqeeekoB0OrGYIcoPAJ9MDsc+j6Yg33Aa91ef13u+HqCHUURAY3T6T3O6Qwe6BgJ/PwFI/6Ok5OjP9CRdeGCoqSnB/8epafrD9yIZMkGO7annldWVuK6667DuXPn0KFDB5SUlOAnP/kJAODNN99Ehw4d0LNnT1RVVeHXv/41Lly4gIqKCiQmJqKkpAT3338/GhsbvY45ZswY9O7dGy+99JLfczY2Nnq9pr6+Hjk5OUw9JwoDvSndRo+jZetWYNSo0I6fk+N/noG6czc0APfe67/Ojp6mpcEKHXpuXLY61Vum63l6uiiGyCwsskLUNAK99NJLsXfvXpw6dQpr167FpEmTsH37dlx++eW466673ONyc3MxePBg9OzZE++++y4KglSkUhQFjiA74hITE5GYmGjq+yAiOWb1rtI6Tqhkjh9ongkJotKwpx/9CCgvb/m6slIUN4yP19e0NFChQ7WdQzhbLuzYETzQAcTz4epDRhSI7XV2EhIS0LdvXwwePBgLFizAlVdeiRdeeMHv2B49eqBnz544+K88xszMTDQ1NeHkyZNe444dO4aMjAzL505E+pnVuyrUjtvHjgV/vqZG7jgy43wDHU/nzwd+nW8tH62O7oAIjsKVn2FFHzIiK9ge7PhSFKXVZSnV8ePHUV1djR7/yvUcNGgQ4uPjsWXLFveYI0eOYN++fRg6dGhY5ktE+pjVuyrUjttar/cswBfKuIaGwIGOLDVY0Fvo0Gpm9yEjsoqtl7Eee+wx3HrrrcjJycHp06exZs0abNu2DZs2bUJDQwPmzp2L22+/HT169MDhw4fx2GOPoWvXrpgwYQIAIC0tDZMnT8asWbOQnp6OLl26YPbs2RgwYABGjx5t51sjogDUNOlA/Z18C9cZPU4gssdPT5c7nta4e++VO04warAQaSspZv0siaxm68rO0aNHce+99+LSSy/FqFGj8Le//Q2bNm3CTTfdBKfTicrKSuTl5aF///6YNGkS+vfvj48//hipqanuYyxZsgT5+fm48847cf311yM5ORlvv/02nNwNRxSR1E7ZgFzhOiPHCUTP8Wtr5Y6pNU62srI/vrV8ZFdI/vIX0XT0t78Vm6WtYtbPkshyYcgMi3iyqWtEZB6z0qQDHWfOnNCOf889cins99wT/Dj5+cZS4/2l4V+4IN6TnnR7rbR3M/Tp4//cffpYe16iqEk9jwTsek5kD5fLf5q0vxTtYJWRAx3Hs+9Tv37AokWiPYKMCRNE7ygt+fnAunWBn29oEFlXWi66yHuzs9ldz+fMARYulB8vK9jma0BUqv7kE/PPSwTIf34z2AGDHaJIEujDU++HZnExsHixd2aS0wnMnCn3of9f/yUCBC2LFgGzZwcfIxMQfPyxfH0cf3V2tDidwJkzIi3eLLKB3OnT8m08iPSQ/fyOuGwsIootevpfBQsKysvF8zKKi0UQ4nsul0s8XlysfYyBA+XOJTPuk08C9+JSgzjPxp4jRgTf51JQABw+DJSVASUlwNSp2nNwuUShQzPJbr42Y5M2USgY7BCRZUpLRRXikSOBu+8W9716icd9yaRol5eLccE0NYkVnWAWL9beuGtW6rnqk0/ECkd+PjBggLg/fdr4JR7P4Eh2g3Yom6X9+VfJM9PGEVnF9grKRNEs0F6RaGLVe9Bb6VfPKkGwPTLLl2sX1VNXOXyrHHsyO9gBxH6h6dNbvtey+4e09Olj7jhZerPgiOzClR0ig/SsWkQqq96DkUq/sqsOWuPMOk7nznLHkR1n5e/LlClyqfpTpoR+Lk+ytVtZ45XsxmCHyAB11cJ3g6i6ahENAY+V78FIpV+zVifMOo5s1WOZcVb/viQkiI3Xwcycae7mZAD4wQ/MHUdkFQY7RDpFWn8iI6x+D0Yq/a5eLfcarXFmrXLIvneZS2bh+H1ZuFBkj/m+d6fTurRzu1aUiPRisEOkU6T1JzLC6vdgpGdShw6BM5ZUQ4ZopzCbtcohu29Ja1w4f1+uvRbw7YGckSEet4JdK0pEejHYIdIp0voTGWH1e1B7JgXamOrbBkElk6Ltj296+4IFoa9yXHON9hiZceH6fVEvlX37bevjWnlpVV1RivP5NLFyRYlIL2ZjEekUC52erX4Pas+kO+4QgY3nJRytnkmffKKvgrK/AnvZ2eL8Z86IrCv1OFOmyK8yZGWZMy4cvy9al8ocDnGpLC8vfNmCLFdLkYQVlMEKyqSPyyWyaLQ6PVdVRW4aeijvQU+qur9AJFAbBCMCpberAdWf/gR07Wosrf7DD4HRo7XHbd0KjBoV+Plw/L5s2yayu7SUlYnaPDJkf85qAcdAuLpDVpL+/La8S1cUYCNQ0mvt2pZGjVrNGyOVkffgr+lmdnbw93vhgqKUlSlKSYm4v3DBnPmrTTG1mmDqmaunkhK5RpslJdrHsvr3xcy5qvOV+Tk3Nrb+Hvv7GTQ2hvb+iAKR/fzmnh0iAwoKRFG8iy7yfjw7u3WxvEil9z0YTZ/W0wZBD62Nv0DrDCc9qd5mXn6y+vfFzLnq+TnrKeBIZCdexgIvY5FxTU3G94RECpnLFeqlmEDBhdmX7mTm9MYbojifXrJzteLyk1XVqs2aq96fc2EhsGyZ9vymTQOWLpV5J0T6sBEokcVKS0WAM2OG+B/+jBni62goKOhJZuUlnOnTspWGjW7olZ2ruskaaJ1VprXJOtgxrVjlMmuuen/OdrWpINKLwQ6RAbFQQVkl05U83OnTMt9XrfR2LTJzjabLlWbMVe/PecoU7e+/w8GigmQ/BjtEOsVCBWWV2asoVqZPA97f12CrGTJk51pQABw+LDKZSkrEfVVVZAU6qlDnGgtlFYj8YbBDpFMsVFAG9K+ipKcHP156eusigXoY+b4GWs0IdrkmUEHDWBHKpTK9xSCXL9eup6Mo/jcoy6woEpmFwQ6RTrFQQTkSV6dC+b76vo+0NHFvxl6bWOhuL0vv3p8DB+SO6zuuLX1PKTIw2CHSKRaW+vWuouzYARw/HvyYx4+Htppl5Puqrk7V1HiPOXlS3Hfp4v243r02gVa/vvkm+vZmydKz96e2Vu6YnuNiab8bRQ+2iyDSSV3q10rztfoySShpzHpXUaqr5cbLjvNH7/dVpkVCUpKocHzsmP7vUbDjq+fQ24LhxAlg+HDRvyorC9i+vXVAFgkKCsT70vr90hugRmJbC2obuLJDpJMVKcl6hXoZQO+H1N/+Jjdedpw/6vc1WHDh+X2VWZ365hsx3sj+FZmihXr2ZmVmin1N+/aJoGffPvF1Zqb8nMJJZu9P//5yx1LHxcp+N4o+DHaIDLAzJdmMywB6N6LKlh4NtUTps8/KPx/KHh+ZzbG+l8YCkRmXmQkcPer/uaNHIzfg0TJlinYA6XS2pJ7Hwn43ik4MdogMsiMl2ayNxXpXp/r1k5uf7Dh/GhqA8vLgY8rLxTjA+N4p2VWx776TO77WuBMnAgc6qqNHxbhok5AAzJwZfMzMmS1VxTt1kjuu7DgiWQx2iEJgVUXcQGQvAyxdqp3Sq2d1KhzF4+69V984vatTgL5VsW7d5OajNW74cLnjyI7TEu6U7oULRWdz3999p7N1x/ONG+WOKTuOSBY3KBNFEdnl/RkzWv6dnS1WcfytOMluRA2HQ4f0jVNXp+64QwQ2nqtd/lan9G6ONWsV4ttv5Y4jOy6Y0lLxHj2DuWA/f7MsXAjMm6fdJ+7LL+WOJzuOSBZXdoiiiJF0djO6kodSPE6WkT5Lelan9G6OfflluflojcvKkjuO7LhA7E7pTkgQweLSpeLeX0PccFwOJfKHwQ5RFDHSD8qMIoF6V12MWL3a2DjZvVN6N8dWVcmN1xq3fbvccQKNa2oSK1SFheK+qan1mEgsEunPokXmjiOSxWCHKIoY7QcVakpvOLpbd+gADBkSfMyQIWKcL5nVKb0bms16z126ABkZwcdkZPivt1NcDCQni8uSy5aJ++Rk8binaEnpTkoSlwmDycsT44jMxGCHKMqol26MXPb4wx+CrxAEMmUKEKfxf4u4uNC7W3/ySeCAZ8gQ8bxRejc0G11p8qe2NnDAk5HhvxJxcbFY4fBdjXG5xOOeAU80pXSvXx844MnLE88TmY3BDlGUMtLpe/Xq4CsEgTidYnwwKSnmbGz+5BPg9GkgPx8YMEDcnz4dWqAD6E+397fnxB/ZcbW1oqVGbq5YxcnNFV/7C3SamoDFi4Mfb/HiloA12lqYrF8PnDkDTJ0KjBkj7s+cYaBD1mE2FlGUUTeihlrAT10hALzTg/3ZsaOlvk0gp0+LcSNGtD6P3myvDh2AdeuCjzFCXRXzl7H029967/OR3Wy9fLnYDyOjSxegslLumFr7a1yulnMPGya+Z8F+RqmpkdXpPSlJBN5E4cCVHaIootWvyQjPFYJAjF4micTu1rIbmsOxKTuQgwf1jXO5xMpIMN9/b/8GZSK7MNghiiIy/Zr0UlcIggmlI3kkdreW2dAcjk3ZgcheolTHLV8ONDcHH9vcHFppAKJoxmCHKAThrlZr1QZTrdWJoUPleiANHSr+HSmp0KH8fO65x9xxelxzjb5xsqtL27eH73eVKJIw2CEyyI5LNFZtMNVandi1S24Pya5d4t+RkAod6s9nwgRzx+mRk6NvnOzq0vr1kXM5kSicGOwQGWDXJRojRQW1eHalDkTvnh27U6HN+Pl8/bXcuWTH6aH+nIPxTJOX6T7uKxIuJxKFC4MdIp3svERjtKhgMJ5dqQPRu2fHzlRos34+WsGG3nF6qD/nYDWBfNPktbqP+4qkyspEVmOwQ6ST3ZdoAvWDyslpaWLpyekUBflkulIHonelwUhHcrOY9fN55BG588mO06ugABg/3v9z48e3zh5buFC7OrGvSKmsTGQ1W4OdFStWYODAgejYsSM6duyI6667Du+//777eUVRMHfuXGRlZSEpKQkjRozA/v37vY7R2NiIwsJCdO3aFSkpKRg/fjy+MTtdhciD3ZdoAP/p04sXAxs3tv4rvbkZ2L1bjFuyBJg2TdyfOSMX6AAiMBo0KPiYH/6wJaDSW8DPTGb9fLRSufWOA+T6XKmKi4ENG/w/t2FD64KQpaXi529EJFRWJrKUYqONGzcq7777rnLgwAHlwIEDymOPPabEx8cr+/btUxRFUZ599lklNTVVWbt2rVJZWancddddSo8ePZT6+nr3MR566CHloosuUrZs2aLs2bNHGTlypHLllVcqFy5ckJ5HXV2dAkCpq6sz/T1S7Nm6VVHE38TBb1u3hm9OFy4oSnZ24Lk4HIqSkyPGGdHYqChOZ/D363SKcZ7Wrm09r5wc8bhVysrkfj5lZcGPY/bPec6c1t9Dp1M87kvv91vr5x/q94IoUsl+ftsa7PjTuXNn5ZVXXlGam5uVzMxM5dlnn3U/d+7cOSUtLU158cUXFUVRlFOnTinx8fHKmjVr3GNqamqUuLg4ZdOmTdLnZLBDekRisBPKB/yFC+LxkhJx7y8gWrJE7vhLlhg7fqgaG8W5p01TlOefV5SLLhIBXqDALztb/HyCzcnMn/OcOcGP4Rvw6P1+y/78zQ6Ciewm+/kdMe0iXC4X/vd//xfff/89rrvuOlRVVaG2thZjxoxxj0lMTMTw4cOxa9cuPPjgg6ioqMD58+e9xmRlZSE3Nxe7du3CzTff7PdcjY2NaGxsdH9dX19v3RujmHPsmLnjzBBKhWN/rRNeeMF7T0go1YTVAn5WKS4Wl/A8L9/FxYmPc4dD3KvUr8+eBUaPbnnc33s26+cs2+dq3ryWjeJ6v99GLkNZfTmRKJLYvkG5srISHTp0QGJiIh566CGsW7cOl19+OWr/1R0vw6dVcEZGhvu52tpaJCQkoHPnzgHH+LNgwQKkpaW5bzmyRS2IEJlNF62ucGxnNeFgAnUGV6sJp6R4P96li7g/ftz7cX/v2ayfs54+Vyq9328jv2vZ2WKju+9GZ6JYZHuwc+mll2Lv3r3461//il/96leYNGkSPvvsM/fzDp/djYqitHrMl9aYRx99FHV1de5bdXV1aG+C2pRQM43Mqrrsudl1zx6RnSU7J73p2XZWEw5EZsXkzBlg82axOXvrVtF80h9/79msjDIjq2L//u9yr+nbV/weuVzaP//sbPE9CNYPLBThriZOpEtYLqrpMGrUKOWXv/ylcujQIQWAsmfPHq/nx48fr/zbv/2boiiK8uGHHyoAlBMnTniNGThwoPLkk09Kn5N7dkivtWuD74UItAHX34bd7Gz9G3b9bXaNi5Ofk949PtdfLzf++uuNfDeNsWpfi+e+JqM/51Dmqec1nrf09NDnapRZv9dEesl+fhte2Tl16hQ2b96M119/Ha+99prXLcTgC42NjejduzcyMzOxZcsW93NNTU3Yvn07hv6rAc+gQYMQHx/vNebIkSPYt2+fewxRpDCr6rLWpZtAnn225d969/iEu5pwQ4NowzBwoLhvaGg9xqp9LWanYWtVp/Y3zkgndd9Lc75C/F9zQIF+r7/5hhWaKYIYiaQ2btyopKamKnFxcUpaWprSqVMn961z587Sx3n00UeVjz76SKmqqlI+/fRT5bHHHlPi4uKUzZs3K4oiUs/T0tKU0tJSpbKyUpk4caLf1PPs7Gxl69atyp49e5Qbb7yRqedkKZk0X98MF7NSw2VSkoPdTp8Wx4nklZ0hQ/wfe8gQ73F6V0z0ZlcZ+Tn7c+qU3HlPndL/3vTezpwJ/efjyazvEZFRlqae9+vXT5k+fbry/fffG5qc6oEHHlB69uypJCQkKN26dVNGjRrlDnQURVGam5uVp556SsnMzFQSExOVG264QamsrPQ6xtmzZ5Vp06YpXbp0UZKSkpSxY8cqX3/9ta55MNghPYxcDjGr9kuoH4LXXy/SrbduFR9SwdKzPT+kjHxgy/BMGV+yRFEGDQp+fM+AR28tGr3Bjlk/MyOBYmOj9mVJI7epU/X9fLSY9T0iMsrS1POamho8/PDDSE5ODmlV6fe//33Q5x0OB+bOnYu5c+cGHNO+fXssXboUS5cuDWkuRLJk97N7jjPrEsrBg3LHCeQvfxE3AEhPFx9F/tKzAe+U5LQ0kfkT7PJKnz5inCx/KeNaysvFJa0OHVr6QS1aFHi8Z9+vIAmaXtRxNTVy47XGffWV3HE8xzmdQHKy/8t3oQj198eXWd8jIqsZ2rNz8803Y/fu3WbPhaKcndkYesrwh+pvf9M/zqw0ZjO7nZ84Ie7VdGxVoJRkrdYSsq0ngMD7jmTce6/3OefMkev79d13csdXx+kdH0g7yT8pPcft2GF+oAMA/fqZezyzvkdEVjO0snPbbbdhzpw5+OyzzzBgwADEx8d7PT8+UPc6ilmyxems4G+FYPZs8Ve9ng9gWZ6rILLj1DTmmhr/r1dTg7XSmK+5Bvjd7+TnKjO/pCSRknzsmAi2hg1rHTyoqerBFBX5b0TqSyZlPBjf1aWFC0VBvuXLxXN9+ojNvr6d3Lt1kzu+Os6nfFdAWuNGjwZeeUX7OJ5FDq3qVRVsFcwIvd9TIrsYCnZ+8YtfAACefvrpVs85HA64WGChTVGzMXw/xNUsIysLl6krBL5crpbHzQ54ZP869hynNsa84w65y0aBWFH/8ptvxHknTgw8RquTONDSPVurWrJMkb1g/BXcS0gQwVYwvl3itcaVl8uNLy8HJk0K/PwVV8gdx3OcFQUp8/IC1xkySu/3lMguhi5jNTc3B7wx0Glb9BanM5NsGX6zL2lNmaIdlDidrVOOCwpE4Of7P349lWyHDrWmtL/WPiQz92YYSav2tHq1sdepq2vBeBYJNLKC54+R3xetgobqazzl5ABDhvgfm5cHrF8ffA5G6P2eEtnF9grKFN20/uJXlJa/+M1mpAy/GRISgLFjg48ZO7b1ZRRABDSHD4sKtkYq2e7aZU3gqLUPycy9GaG0lBgyRGxONkJdXQtWZdhzdc3ICp4/6kbqYDw3UnvOVZ2X7zwdDmDNmta/R598IqpGT50KjBkj7s+csSbQ8ZynOid/82TvLYoEhoOd7du3Y9y4cejbty/69euH8ePHY4cVn2gU0ewq1AaE1pwyFC4X8M47wce8807goERtjDlxorjX80Fg1V4OrdUJM/dmTJlibKP1kCHiw9wf2c3x6uqa72pETk7r1TWjK3j+6NlI7TvXQCuBEyb4P1dSErBsGfDBB+Le7EtXeufJ3lsUCQwFO6+//jpGjx6N5ORkPPzww5g2bRqSkpIwatQolJSUmD1HimB2NsW0qznl++/LrSi9/7655wWA7t3NPyagvToR7r0ZDgcwfjwwYACQnw+cPh040CktBXr1AkaOBO6+W9z36hW4cq/s6pqRFZlgFi4UqyxLlgDTpon7M2eC7ykLNFdA33u2WqgrlkSWM1LE57LLLlMWL17c6vHnn39eueyyy4wc0lYsKmicWkFVtjidmWQKr8XFtRSVM0v//nKF1Pr3N/e8iiJfGE/vTet7ZGalXNnCiFOnigKIZWWBj7t2rf/fPYdD3MzozeSvD5nTKR63QzjeM1G0sLQ31pdffolx48a1enz8+PGoUv/soDZBa28BYN01e7XwWjDJyeafW61PY9Y4PY4dM/+YgPZKlefPORDZn7PsZcXf/S74qkW4NscvXChWljz3wZw+bU1ZAy12JgQQRTNDwU5OTg4+/PDDVo9/+OGHyLEiN5Yiml3X7GUKrzU0mL85OiXF3HF6WHE5EBD7RrT89a+hPa8yclnRX7PUcG2OLy0F+vcXwdfmzeK+f397LhnZmRBAFM0M1dmZNWsWHn74YezduxdDhw6Fw+HAzp07sWrVKryg9ecfxaSCApHeumOH2EQbqDidmezaHD16NKDR6cQ9zmxaxQmN+r//C/68bJr/vHnae1imTBFFH/WsPqhtLTwLF8r+XD/80PjvpJ01pPyxMyGAKJoZCnZ+9atfITMzE88//zz+9Kc/AQB+8IMf4M0330ReXp6pE6TooWYZhYtdm6Pbtzd3nB7q5aTbbzf3uFqXx/Sk+WsV95PpaeWP56rFiBHyP9d581r+raeqt9YlI9/gS0ZTk3al52DsTAggimaGU88nTJiAnTt34vjx4zh+/Dh27tzJQIfCSqvwmsNhTUGza64xd5xespeL9MjICP682Wn+gVKxZairFjKF93x9803ry2GBmH3JqLhY7CGbMUOkhM+YIb4uLpZ7PWDf7zxRtGNRQYpadm2O7trV3HF6hNpXKpDLLgv+vBVp/r6p2FOnyr1OXbUI9vMPRlHkNvGaeckoUONTta2JbMBjZ0IAUVSTTe/q3Lmz8t133ymKoiidOnVSOnfuHPAWbZh6bo4LF0SasFa6sNnWrm2dFp2TEzwFN5S5jhsnlzo9blyo76w12bRtvbexYxVlwABFyc9XlNOnW5+3sbF1+rXvzekMLc3faBkDfz9/mVtZWfD5lJWZcxwrvndGfueJYpHs57f0np0lS5YgNTXV/W+HkRKoFLPs7Hqud3N0qHPdt09uXrLj9Pj8c/OPCbRUhK6sBFJTW1crltlno6fAnj9Gm6X6/vz37QPmz9c+n1YfL7M61Zu530llR0IAUVQLU/AV0biyE5poKnJmxlwHDZL7i3/QIPPnn59vzcqOv9uQIa3PH44Ce6GuWsiufi1ZIjcX9XfD6O/LtGly85k2Te79EVELS4sK7tmzB5WVle6vN2zYgPz8fDz22GNoMrvFNEW0aCpyZtZc586VO5/sOJVMfyetjcRa4uNFCwatRqYAUF7euo6RkZYHwTQ1idWawkJx39QUeusBM/t4mVFDyq62JkTkwUgkNXjwYOWtt95SFEVRDh06pCQmJioTJ05U+vbtq0yfPt3IIW3FlR3jzNrXEA5mzVW2ZcPWrfJz87eakZ3deuVg6tTwrewAYiXJKlatElnxOxnKHq9w7HciaqssXdn5/PPPcdVVVwEA/vd//xfDhw9HSUkJVq1ahbVr15oXiVHEi6YiZ2bNVbZlg+w4tXCdb5qzv6rBVqWzB2J2x3iVWdlJ/qh7bYLRm54dSqd6sxuKEpF+hoIdRVHQ3NwMANi6dSt+8pOfABBtJP75z3+aNzuKeNFU5Ey2Y7jWOLOOA+i/tBbqZSy9rLi0IluN2egVcTP7eJnl2mtDe56IQmMo2Bk8eDDmzZuH1atXY/v27bjtttsAAFVVVcgI9/+NyVYschYavYXrPLbKhcXq1eYfU092klFm9fEygxrQBqJWYo6EfW1EscpQsPPb3/4We/bswbRp0/D444+jb9++AIC33noLQ4cONXWCFNki8a/oQMy6/BTqcTw3Ivvpp+uXemntyy/lxpthyBCgQwfzj3vwoLnjfFm9cqQXm3cS2c9Qb6yBAwd6ZWOpFi1aBGckfKpRWBUUiMaOixd7/3XqdIq9COFslBiMWZfcQjmOvxo/eo4VrvJWvnV2zCT7Hoy+Vyvq2oQimva1EcUqQys71dXV+Mbj/9affPIJioqK8NprryE+Pt60yVF0KC0F/uu/Wn/ANDeLx2X6EIWDWZfchg3TXvFITW19nEAbkYPxnZNVG5R79RIp6fn5wOnT1gU6gPW9xczu4xWqaNrXRhSrDAU7d999N8rKygAAtbW1uOmmm/DJJ5/gsccew9NPP23qBCmyRVOdHbP6CrlcorZMMN9/7/2eg32fAvE3p6ws+dfr8dBDwKefAuvWWXPpylNOjrnjfEVaXRvuayOyn6FgZ9++ffjRj34EAPjTn/6E3Nxc7Nq1y51+Tm1HtO1HMKNI3PLlYtUqmOZm7w22Wt8nf/TMKVTh3AtkRWq4pylTtANWp1OMCwc27ySyn6Fg5/z580hMTAQgUs/Hjx8PALjssstwhBee25Ro3I8QaoVeI5dJZN//E08En1Ntrdxx9Kqqsua4/qgf/sFWOkL58E9I0K4QPXasvro2MtWtgzEjyCYi4wxtUL7iiivw4osv4rbbbsOWLVvwn//5nwCAb7/9Funp6aZOkCJbtO5HUIvEGWHkMoxsbZ4RI4BRowI//+23csfR619/u4SN+uHvu1k7J0cEOqF8+LtcQEVF8DF79ohxMgGVWU1u2byTyD6Ggp3nnnsOEyZMwKJFizBp0iRceeWVAICNGze6L29R2zBsGJCeDhw/HnhMerp5+xFcLv8fFoEet4LsKogVqyX/+If5xwTEHiNZZn2vrfrwl7lkqF5a1Qp41U3lvnut1OrWeldlQgmyicg4Q8HOiBEj8M9//hP19fXo3Lmz+/Ff/vKXSE5ONm1yRJ4C/YU9caK4vBDqX96yjFzGMqvGj56gRI+6OrlxZq1yqKz48Dfr0qrW5nu1GGBeHldniCKdoT07AOB0Or0CHQDo1asXusuu11NM2LEj+KoOIJ4PdYNyoLTtb74RvZT8Pe7bV8osKSn6x8lexjt6NPi+EKsydhobtfej6OnhZSezLq1G2+Z7u4W6r4nIStLBzg9/+EOcPHkSAHD11Vfjhz/8YcAbtR3h2KBsJG0bEOOtSHv/Vys4XeOGDpX763/GDODuu4GRI0XtG98AYvJk6Wnqsn9/8PNGU4kBs1K9o3HzvV1KS8XvzciRwX+PiOwifRkrLy/PnYGVn59v1XwoyoRjg7KRtG2V7N4MPd57T37cL34h/r1rl/5AwN++kMcf13cMI/ydV88qh917UtRsrzvuEIGNZ4CmJ9U7Wjffh5vZ+5qIrCAd7Dz11FN+/01tm/pXdE2N/7/6HQ7xfCiXX0L9y7mmJrTX+6qv1z/OyBz87Qs5cED/ccw4b7StcgTK9srOls/2CsfvdrTjviaKFob37KgaGhpQX1/vdaO2IxwF00L9y/m770J7vS8jm42NzsF3X8jZs8aOE+p5o3GVI9R6SiwGqI37mihaGAp2qqqqcNtttyElJQVpaWno3LkzOnfujE6dOrXatEyxz+qCacOGAaG0XOvWLbTz+8rI0D8u1Dl8+KHY+Bnu/7zUlZpobXmgZntNnCju9QYmLAYYXLSt+FHbZSj1/J577gEA/OEPf0BGRgYc4WrFTBHLyoJpZ88C588bf73vB1Wo+vYVwYfMOLPmMG9eaK83Sk2uNGsfTDRiMcDAonHFj9omQ8HOp59+ioqKClx66aVmz4eimFUF0+691/hrA602hFIY75JL9I+TKb4Y6czYBxOtWAzQP+5romhh6DLWkCFDUF1dbfZciPz64gv9r3E4AvdYCjVN1s4KyuHm254i1H0wFFu4r4mihaGVnVdeeQUPPfQQampqkJubi3ifDRUDBw40ZXJEAJCWpv81gVYbzEiTrayUm4PnOJnii5Hob39rvbLGVQ7y1JZX/Ch6GFrZ+e6773Do0CHcf//9GDJkCK666ipcffXV7ntZCxYswJAhQ5Camoru3bsjPz8fB3xya++77z44HA6v27XXXus1prGxEYWFhejatStSUlIwfvx4fGO0MAsZZlUF1fvvlxs3e3bw1QazCuPJNs30HBetGzQjoUggRT6u+FGkM7Sy88ADD+Dqq6/GG2+8EdIG5e3bt2Pq1KkYMmQILly4gMcffxxjxozBZ599hhSPWvu33HILVq5c6f46ISHB6zhFRUV4++23sWbNGqSnp2PWrFkYO3YsKioq4OT6aViY3TPJ0+nTcuMuukhk3QRiVmG8xka5+XiOi9YNmvzPh2RxxY8imaFg56uvvsLGjRvR1zPdxIBNmzZ5fb1y5Up0794dFRUVuOGGG9yPJyYmIjMz0+8x6urq8Pvf/x6rV6/G6NGjAQCvv/46cnJysHXrVtx8882tXtPY2IhGj08i1gYKTaBLQ2p/qlBTdGXTtrXGmZUmO2AA8Je/aB9nwICWf0frBuVrrrF7BmRWl3mitszQZawbb7wR//jHP8yeC+r+1Xq5S5cuXo9v27YN3bt3R//+/fGLX/wCxzyqtVVUVOD8+fMYM2aM+7GsrCzk5uZi165dfs+zYMECpKWluW85OTmmv5e2QqtvlRn9qWTTtrXGmZUmK5uEGAvJigH+xqAwYc8pInM4FEVve0Xg5Zdfxrx58/DAAw9gwIABrTYojx8/XvdEFEVBXl4eTp48iR0e5TbffPNNdOjQAT179kRVVRV+/etf48KFC6ioqEBiYiJKSkpw//33e63UAMCYMWPQu3dvvPTSS63O5W9lJycnB3V1dejYsaPuubdl27aJ/wFrKSszvsTtcgGdOgENDYHHdOgAnDoV/C9el0t8UGilyVZVBT9OUxOQlAQ0NwceExcn6gOpV1xlv0+R5vnngZkz7Z5F2xRoxVTdNcCihkTi8zstLU3z89vQZayHHnoIAPD000+3es7hcMBl4M/4adOm4dNPP8XOnTu9Hr/rrrvc/87NzcXgwYPRs2dPvPvuuygI8l+6oigB9xIlJia6m5pSaL76ytxx/rhcwJkzwcecOSPGBQtSzCqM53QCycnBg6/kZO/jROsG5VhIn49G7DlFZC5Dl7Gam5sD3owEOoWFhdi4cSPKysqQnZ0ddGyPHj3Qs2dPHDx4EACQmZmJpqYmnDx50mvcsWPHkCFb158MW7/e3HH+LF8efBUFEM8vX659LDPK/+/YETzQAcTznv2AonWDcp8+ds+gbWLPKSJz6Qp2fvKTn7j31QDAM888g1OnTrm/Pn78OC6//HLp4ymKgmnTpqG0tBR//vOf0bt3b83XHD9+HNXV1ejxr0+PQYMGIT4+Hlu2bHGPOXLkCPbt24ehQ4dKz4WM+f57c8f586+41rRxoabJGtnorFaaDSY7G9i6VczpiSfkzmG1Bx+0ewZtE3tOEZlLV7DzwQcfeO11ee6553DixAn31xcuXGhVJyeYqVOn4vXXX0dJSQlSU1NRW1uL2tpanP1Xa+eGhgbMnj0bH3/8MQ4fPoxt27Zh3Lhx6Nq1KyZMmAAASEtLw+TJkzFr1ix8+OGH+Pvf/46f//znGDBggDs7i6zTv7+54/yRrWygpwJCKA0ijWx0djqDp8UD4vlRo1ruI8Hf/mb3DNom9pwiMpeuYMd3L7OBvc1eVqxYgbq6OowYMQI9evRw3958800AgNPpRGVlJfLy8tC/f39MmjQJ/fv3x8cff4zU1FT3cZYsWYL8/HzceeeduP7665GcnIy3336bNXbCwM+2rZDG+SOb/tyxo/kFDf0x0gHc5RJzC2bNmpZ5a50jXLhyYI9o7TJPFLEUHRwOh3L06FH31x06dFAOHTrk/rq2tlaJi4vTc8iIUFdXpwBQ6urq7J5K1Jk6VVHEDoLgt6lTjZ+jrEzuHJ637GxFWbvWtLfZytq1iuJwiJvnedXHfM8t+x7KyrzPofd9a93y8xWlpERRlizRPx8KL72/Y0Rtkeznt66VHbVdg+9j1HaZvZ/GH5n9Lr7UXleB6pGE2tpC3ejsexkhK8v/RmcjezD++ld9c5Jx5oy4TFZYyJWDSGfGZnoiEnSlniuKgvvuu8+dtn3u3Dk89NBD7tYOvrVuKPb16wds3iw3zig1Zfz22+VfEyw916zWFq+91roreE2NeNz3OHr3YDQ1AYsXy89FlvpzMCsNn6xVUCB+f1lBmSg0uooK3i/ZkdGzj1U0kC1KRK2dPStqymg5c0YU4jOquBhYtMjYaz0LGgYq1AaID3nZv5jz84ENGwI/n5fnnW6vt6Dhb38LzJihPQ+9nntOpCz36QNMmQK8807rwC8nh92qiSg6yH5+G6qgHGsY7BjX1CTXBbyxsaWasJFzJCcb33RcUiIu3agBR7D6JTk52hWUjQZ4paXBV6fWrm0JMKZOlasbFAqnU1RHXrCAKwdEFJ1kP78NFRUkUsl+IIfywb18eWjZVeqlIa1CbYBcobY5c+TOKzvOn3BshXO5xGrZo48aT8MnIooGDHYoJPv3mzvOHx2lm7z4brKtrpZ7nda4zz+XO47nOLX8fyDq/iI1qAtnt/HFi8XqGRFRrGKw04aEmoHkj2zGUCiZRZWVxl/ruclWtkCe1rh/7cfX5DlOb/n/nBy5c5jB5bL+khkRkZ0Y7LQRpaViv8rIkcDdd4v7Xr0Cp2ZHEqMbm8eP995kK7s7TWtcfr7ccTzH6U09N5JuH4pDh8J3LiKicGOw0waoGUi+KwtatWhk9O0rNy4tzfiK0qWX6p4WAJEtVVzc8rVs+rvWuJ495Y7jOU5v6rnTCQwaJPcaM7DhJxHFMmZjIbazsbQykHxTnvU6cQJIT9f3Gr01berqgE6ddE8NgHhPZ86ITDCZrC7P8YEYycbSm3oeagaaHjLvmYgoEjEbiwDo3yui12uv6X+N3hWlUMo2ee5HSUgAxo4NPn7sWO0P/Zdekju35zi1iB/QOtPKXxG/UDPQ9Jg5k4EOEcU2BjsxzkibAj2MZFmpKxue2UfBhLJBGWjZj+JyARUVwcfu2aM9JyPZWIC+8v/h2EPjdIr0+IULrT8XEZGddLWLoOijd6+IXlu3Gnud54qSWt04kHXrjJ1Dpe5H0VNnJ9icQgkgZcv/W7WH5vrrgauvbqmgzBUdImoLGOzEODWrR2uviNGGj+fOhTY/mcAh1JZrDz4o7mtq5MZrjevaVe44gcY5ndoB3pQpwOzZ5l/KSkkBli4195hERJGOl7FinLpXJNA2dEUJreFjQ4PhqQGQW1FKTQ3tHGrdnO++kxuvNe7oUbnjyI7zJyFB7KUxWygNWYmIohWDHQpJWpqx1/lWNw7mN78xdg6VunrUrZvceK1xsq0cQm35cO21ob3eH6PNVImIohmDnRin1aYAkN8o7I+RvT7+so+C6dVL/zk8qWnrvhuDA9EaJ1udIJQqBjI/N73y8kLrPE9EFK0Y7MQ4s5pfBmLkUo2/7KNgNmzQfw5PGzeKe5mqxDKrTT/7mdx5Zcf5I/Nz02PIEGD9evOOR0QUTRjsxDizNuUGcuKE3LjERKCkBCgrE4XzZAMdIPQ0bDUFXN2/FOjyksMht9ok25jUaANTwHgpgEB2746O1iBERFZgsBPjzNqUG0iHDnLjOnUCJk4UWUh6N0OHuqn2yy9b/q3WuvFd4cnJkV9tqqqSO6/sOH+MlgIIJpTLlURE0YzBToyTbeWgt+WD6pFHzB3nT6iban27lBcUAIcPi1UmI6tNsjVwQqmVo15yC3WTsyrUStlERNGMwU6MO37c3HG+/vAHc8f5k5QkNtca5W9lSK11Y2S1acoU7fFOpxhnVLD2EqEw+/IYEVE0YLAT40JJt25qEntYCgvFfVNT6zGnTskdX3acFVavNvd4MjVwzOg3Fai9RCisuDxGRBTpGOzEOKPp1sXFouv2jBnAsmXiPjlZPO4pJ0fu+LLj/Dl71nhGVkKCNenWCxeKvlK+Kzxm95vyveR2/fXGjqOnrhERUaxhsBPjhg3T3o+Tnu79IVhcLPbJ+G5mdbnE454Bj1YXcb3j/Jkzx/hrm5qs26eycCFw5gywZAkwbZq4P3PG/MaanpfcNm3S/3q9dY2IiGINgx3y0tQELF4cfMzixS2XtL76Su64suP82bfP+GsBsTHXKk4ncNVVwNCh4t7qYKJDB1EzJ5j4eO+v9dY1IiKKNQx2YtyOHdqbj48fb1n9WL5cOz3Z5RLjAGD/frl5yI7z5//9P+OvBVp6Y3mS2Y+kpbQU6NkTGDkSuPtucd+zp/X1bP7jP4I/r2aYGa1rREQUa9j1PMbpLSooW8BPHee7ihCI7Dh/2oX4W+rbBLW4WKxOeQZ1s2eLTcWyl6BKS4Hbb2/9eE2NeHztWmsCDK02Eg6HeB9VVbxkRUSk4spOjNNbVFBvDZnDh+XGy47zJ9TeWJ6p53r2IwXicgG//GXwMb/8pTUF/LTaSLCeDhFRawx2Ypze1HO9NWTat5c7vuw4f9atM/5az7nq3Y8UyLZtcpcGt22TnaU82To5rKdDRNSCwU6M05t6rreGzLlzcseXHefPH/9o/LWec9W7HykQ2SDGimBHtk4O6+kQEbVgsBPjjHT6VmvIxPn8dsTFta4h07u33Dxkx/ljpBGov3o3evcjRSIjpQSIiNo6BjsxzrPtQCD+6q9ce23r1YEePcTjnjIz5eYhO84frWDNH5erpdu5yqyeViNGyB1HdhwREVnLoSi+uSptT319PdLS0lBXV4eOHTvaPR3T/ehHQHl54OeHDAE++aTl69JS4I47WmcxqcXpPGu2tG8PNDZqzyEx0filrIceAl56ydhr8/KA9evFv5uaRBXoYJeynE5RGDBYqweXC8jICL5vJz0dOHrU/IyobdtEiruWsjIGW0QU+2Q/v7myE+MaGoIHOoB4vqFB/FtNbfYXAiuKuBUVtQQMMoGOnnH+VFUZf+2GDaLdBGBeTyunE3j55eBjXn7ZmtRvblAmItKPwU6Mu/defeO0UpsB79Rm2Y7coXTu9te1XA/PdhNm9bQqKBC1dHwvsWVnW1djB+AGZSIiI1hUMMZ98YW+cXqLEPbr13pvjD+hBCyLFgG/+53x1x844P31woXAvHki6+rQIbFHZ8oU/V3KCwrEZbIdO8RKSo8eYmOwlcX81A3nNTX+V98cDvE8NygTEbVgsBPj0tL0jdNbhLBbN7lgR7bejz9JSSKoMNr5XL2M5SkhQVyOC5XapDNc1A3n/qo3AyIAYsNPIiJvvIwVxVwusWH1jTfEvb+Nt5Mnyx1LHae3CKHe4xvVv7/x1w4YENq5iYgoujHYiVKlpaKNgmcTyl69Wjeh1FsHR28RQr3jjZCpfBxM377GXxtpZHpjeW4gJyIim4OdBQsWYMiQIUhNTUX37t2Rn5+PAz4bLBRFwdy5c5GVlYWkpCSMGDEC+31aaDc2NqKwsBBdu3ZFSkoKxo8fj2+0dtlGMTU13Pct1tSIxz0DHr1F6PSOr6yUm7PsOH9kKh8HE0srO+yNRUSkn63Bzvbt2zF16lT89a9/xZYtW3DhwgWMGTMG33//vXvMwoULsXjxYixbtgzl5eXIzMzETTfdhNOnT7vHFBUVYd26dVizZg127tyJhoYGjB07Fq4Y/PNWKzUcCO9f9jL7dfSM88d3g7FeWn2soglTz4mIDFAiyLFjxxQAyvbt2xVFUZTm5mYlMzNTefbZZ91jzp07p6SlpSkvvviioiiKcurUKSU+Pl5Zs2aNe0xNTY0SFxenbNq0ye95zp07p9TV1blv1dXVCgClrq7OwndnjrIytdpN8FtZWXjG5+bKjc/NNf6e8/PlzqE111ig9+dDRBTL6urqpD6/I2rPTl1dHQCgS5cuAICqqirU1tZizJgx7jGJiYkYPnw4du3aBQCoqKjA+fPnvcZkZWUhNzfXPcbXggULkJaW5r7l5ORY9ZZMp/cve73j9aaey64ghbLS1L278dcCwDXXhPb6SKKmngeqW+RwtO51RkTU1kVMsKMoCmbOnIkf//jHyM3NBQDU1tYCADIyMrzGZmRkuJ+rra1FQkICOnfuHHCMr0cffRR1dXXuW3V1tdlvxzJ6i8rpHa839fyf/5QbLzvOn2PHjL8WMN5qIhJ59jrzDXjUr5l6TkTkLWKCnWnTpuHTTz/FG2+80eo5h8//1RVFafWYr2BjEhMT0bFjR69btDCy4bh9++Dj27dvGa839dy3M3ogFy4ET5EPJtRqwJHcxdyIggLRn8w3wy0727tvGRERCRER7BQWFmLjxo0oKytDtkf9/cx/tcr2XaE5duyYe7UnMzMTTU1NOHnyZMAxbVlTk3YDznPnxDhAfxdzrUBKdfJk8BT5YGS7lVv1+khUUAAcPiwafpaUiPuqKgY6RET+2BrsKIqCadOmobS0FH/+85/R26coTO/evZGZmYktW7a4H2tqasL27dsxdOhQAMCgQYMQHx/vNebIkSPYt2+fe0ws2bFDO7vo+PGW1GPPvlDByI7z5S8rTIu/FPlgQkkddzpFK4hYpFZvnjhR3PPSFRGRf7a2i5g6dSpKSkqwYcMGpKamuldw0tLSkJSUBIfDgaKiIsyfPx/9+vVDv379MH/+fCQnJ+Puu+92j508eTJmzZqF9PR0dOnSBbNnz8aAAQMwevRoO9+eJfRuOD54UG68Ok52f4w6zsjGY0VpKX6Xl6f9IR1K6rhMF/NQuFzh7Y0VKecmIooqYcgMCwiA39vKlSvdY5qbm5WnnnpKyczMVBITE5UbbrhBqays9DrO2bNnlWnTpildunRRkpKSlLFjxypff/219DxkU9ciwQcfyKUef/CBGD91qtz4qVPFeL2pzddea31auOycPG9Op6LMmWP+99/T2rWKkp3tfd7sbPG41ew8NxFRpJD9/HYoipELEbGlvr4eaWlpqKuri/jNys8/D8yerT3uv/4LmDVLNMFMTtYef+aMaLjpcgGdOgENDYHHpqaKPThOJ3DffcCrr8rOvrWSEnEZJhiXS+zzCdbpu0cPYPx44MsvRYf1RYvE+7GKWsXadz7qnngrNwrbeW4iokgi+/kdERuUSZ5sZpE6zl/Hb3/UcS6XCHyC+f77lstX+/bJHT8QmUwrNd06UFiuKEBjI/Dii8DmzcDvficah+rZBK2HnVWstc6tKOyNRUTki8FOlNG7Z2f4cLnx6rjly4Hm5uBjm5vFuFCYXfzOd1+P3k3QetjZn0rr3AB7YxER+WKwE2X0poZ/+63ceHWcT4/VgNRxI0bIjfekt/idVqdvf6xcYbGzP5Vs/csoqpNJRGQ5BjtR5tJL9Y3LypIbr47761/lxqvjPHq2StNb/E5mNcMfq1ZY9FalNtPf/mbuOCKitoDBTpSZMkW7anFcXEttme3b5Y4rO87fuWTk5RkvfhfqConZKyx29qeSTSdg2gERUQsGO1HG6dTOrkpJabk81KGD3HHVcX37yo1Xx118sdz4664zXvwu1Eagob7el539qfr1M3ccEVFbwGAnyuzYETwtHABOn265dCO7kVgdt3q13Hh1XFWV3HjZcdHCrv5UU6ZoB1GxXDWaiMgIBjtRpqZG37i9e+XGq+OSkoD4+OBj4+Nbath88YXc8WXH+RNq13Of1mqmsaM/VUKCqAodjNVVo4mIoo2t7SJIv+++0zeupERufEkJsGqVWBE6fz742PPnxbgRI4CjR+WOLzvOn1A3+sp+z4xQ+1OF08KF4n7xYu9MM6dTBDrq80REJDDYiTKdO+sbd+GC3Hh13FdfyY1Xx2VkyBUWDKUB/dCh4oPcaAp5t27Gzx2pFi4E5s0Tlx8PHRKd3adM4YoOEZE/vIwVZcrL9Y1LSZEbr45bv15uvDrussvkxsuO82fXrtBq5fjuq4kVCQmijtDSpeKegQ4RkX8MdqKMbErx3r1AYSHw8MNy49UigbJ1c9RxixbJjZcd508oqeNWpYATEVH04GWsKCO7SvGXv4ibLHVVoG9fYMsW7fFq6rlsenUoadih7NmxKgWciIiiB1d2osw771hz3KuuEvfjx8uNV8fpTW03QquIX1vV1CSCucJCcd/UZPeMiIgiE4OdKGOkbYKMkye972XHHzggN152nD/BivhpidUO4MXForjkjBnAsmXiPjlZPE5ERN4Y7EQZ2YrFeql7gfT2fZKtYRNqrZtARfy0xGIH8OJisQfKN4hzucTjDHiIiLwx2Iky775rzXF79xb3evs+hbMppm8Rv8cek3udbCHGaNDUJOrrBLN4MS9pERF5YrATZdLSQqtZE4j64ai371P//nLHlx2nRS3iN3GifP0cK4sKhtvy5dqX5Vyu0PZIERHFGgY7Ucblki8UqIe6sgO0XDLKyvIec9FFrfs+2dmrSTbYiaWigocOmTuOiKgtYLATZbZtA44fN/+4l1/e+jGZzcB29mqS3b8TS0UFe/UydxwRUVvAYCfKbNtmzXE9i/6VlgJ33NE686umRjxeWur9+MKFwJw5rVd4nE7xuFW9moYNA9LTg49JT4+tooIDBpg7joioLWCwQ8jLa+li7nIB06f7r9SsKOLmL5174ULgzBlgyRJg2jRxf+YMm1KaTXZVz4rVPyKiaMVgJ8qY3WE7L8+7H9aOHdq1fAKlc7tcwBdfAJ9/Lu6trm+zY4f2h/rx47GVeh7O7DcioljBdhFRZujQ0F4/apS4vNSvn7h0pa7oqGTTtH3H5ecDGza0fL15M/C737UOpsxUXW3uuGiglgaoqfG/+uZwiOdj6dIdEVGouLITZV56KbTXjx0LfPCBqLrrG+gA8mnanuN8Ax1PGzaI563wt7+ZOy4a6C0NQEREDHaizsGDob1eKw1ba8Ov77izZwMHOqoNG8Q4s8l2gJcdFy0CVZPOzm5dGoCIiHgZK+qE2gxTKw1b7wZYrbRz1cyZwIoVcmNl9etn7rhoUlAgLhHu2AEcOSL26AwbxhUdIiJ/uLITZa65xvhr09PFpuE33hAp7P42EOst1Ld7t9x42XF62FnQMBJ4VpMeMYKBDhFRIAx2okxOjvHXnjwJjB4N3H03MHKkKDznWzMnM1PuWOq4Tp3kxsuO08POgoZERBQ9GOxEGTUbx4jmZu+vAxUJ1OPGG80dp5ddBQ2JiCh6MNiJIC6XuLwU7DKTmo3jcIS+f0fduOtZJPDbb+Veq447dUpuvOw4I1jQkIiIgmGwEyFKS8VlpZEjg19mAgJn4xihKN5FAvWmc+/ZIzdedpxRCQkiaFu6VNzz0hUREakY7EQAvb2oABHwHD4MlJUBJSXA1q3yaeP+HDki7vWmc6ekyI2XHUdERGQ2Bjs20+pFBfjvRQW0zsYJhdpeoE8fufHqONlKvazoS0REdmGwYzOtXlS+l5mCHcdI80eHQ2R4qcGI3q7ahYVAnMZvUVycGEdERGQHBjs2Uy8fhTpO9jie/LUX+Oc/5V6rjktIAGbNCj521izuoSEiIvsw2LGZWV2sjXS59tdewMh8mP5NRESRzKEosdY5SL/6+nqkpaWhrq4OHTt2DOu5XS6RdaXVxbqqKniFXJnjZGUBM2aIjc19+ojKwr4rLqHMp6kJWL4cOHQo8PGJiIjMIvv5zWAH9gY7QEs2FuAdYKiXmWSbOwY7jqKIbC3PfT3Z2aJmj++xzZoPERGRlWQ/v3kZKwKY1cU60HG6dBH3vhuYA6W2s6s2ERHFEluDnY8++gjjxo1DVlYWHA4H1q9f7/X8fffdB4fD4XW79tprvcY0NjaisLAQXbt2RUpKCsaPH49vgqU3RSjfujllZeJSkd7Awl/9naQk/2ODpbabNR8iIiK7tbPz5N9//z2uvPJK3H///bj99tv9jrnllluwcuVK99cJPptAioqK8Pbbb2PNmjVIT0/HrFmzMHbsWFRUVMAZZW2g1bo5Zh5n2zb51Hbfc5s1HyIiIjvZGuzceuutuPXWW4OOSUxMRGaAVtx1dXX4/e9/j9WrV2P06NEAgNdffx05OTnYunUrbr75ZtPnLMvlEgHEkSMic2nYsOAbjI2+RotZqe1ERETRKuL37Gzbtg3du3dH//798Ytf/ALHjh1zP1dRUYHz589jzJgx7seysrKQm5uLXbt2BTxmY2Mj6uvrvW5m0tPnKpTXyDArtZ2IiChaRXSwc+utt+KPf/wj/vznP+P5559HeXk5brzxRjQ2NgIAamtrkZCQgM6dO3u9LiMjA7W1tQGPu2DBAqSlpblvOTk5ps3ZSJ8rI68JxrN7usslNhYH6pDuW0E5FDJd26PhHEREFGOUCAFAWbduXdAx3377rRIfH6+sXbtWURRF+eMf/6gkJCS0Gjd69GjlwQcfDHicc+fOKXV1de5bdXW1AkCpq6sL6T1cuKAo2dmKInbCtL45HIqSkyPGhfKaYNaubX289PSWY/ke2+EQrwmVv/NmZ5tz7HCeg4iIokddXZ3U53dEr+z46tGjB3r27ImDBw8CADIzM9HU1ISTJ096jTt27BgyMjICHicxMREdO3b0upnBSJ8r2dcsXaq9mhFohejECXGvpqCrzEolN3tlyq5zEBFRbIqqYOf48eOorq5Gj39tMBk0aBDi4+OxZcsW95gjR45g3759GDp0aNjnZ2QzsOxrZswIvpdHq3u6wyFS0LduNTeVPJSu7WadQ1FCPwcREcUuW4OdhoYG7N27F3v37gUAVFVVYe/evfj666/R0NCA2bNn4+OPP8bhw4exbds2jBs3Dl27dsWECRMAAGlpaZg8eTJmzZqFDz/8EH//+9/x85//HAMGDHBnZ4WTkc3ARjYG+1vNkFkh+uYbkd01caJIKTcjM9+sru2hnAMI/RxERBS7bA12du/ejauvvhpXX301AGDmzJm4+uqr8eSTT8LpdKKyshJ5eXno378/Jk2ahP79++Pjjz9Gamqq+xhLlixBfn4+7rzzTlx//fVITk7G22+/bUuNnWHD9G8G1nqNP/5WTOxKMQ/HeWtqzB1HRERti611dkaMGAElSGuuDz74QPMY7du3x9KlS7F06VIzp2aI0yl6Td1xR0s/KpUazPz2t94rKsFeE4xvMUC7UszDcd7vvjN3HBERtS1RtWcnGhjpKxXoNTLUFRMjq0pmCMd5u3WTG7d7N1BYKALKpibj5yMiotjCYMcCRvtKGek/r66YqCtEQOvAI9CqkhnU8waau6KEfl7ZIPCPfwSWLRObuZOTgeJi4+ckIqLYYetlrFimp6+UmlatJ9hxOMSKiueKibpCNH2694beiy4SAUm0NvFUV4/09Hd1uYBFi8S/Fy60Zl5ERBQduLJjs2Bp1YFordT4HsvIipEsdf6BOByhp4Wrq0d6NnGrFi/mJS0ioraOwY7NZNKqfQXa/6OuEPlmJX37rXWF98KReg60rFplZ+t7ncsFLF8e2rmJiCi6MdixmWxK9hNPBN//E47ifv6EM+Xddy9Ufr7c6w4dCv3cREQUvbhnx2ayKdmjRgXfA6RnhUV2L5GMcKe8e+6FOnoUWL9e+zV9+phzbiIiik5c2bGZWanbdhUVtCvlHQCmTNHO8nI6xTgiImq7GOzYzKyUcbuKCtqV8g4ACQnAzJnBx8ycKcYREVHbxWAnAhgpROjLihUWl0t0Wdfqtm7G/I1auBCYM6d1MOV0iseZdk5ERA4lWL+GNqK+vh5paWmoq6tDx44dbZuHyyX21Bw5IlZghg3TtyKiZmMB/ltV6Ak8Sktb1+vJzg5eryfU+YeiqUlkXR06JPboTJnCFR0iolgn+/nNYAeRE+yYwV+QkpMjLiXpCXT8FTk0EjQRERFZhcGODrEU7AChrbC4XECvXoEzu9TKzVVVrY9p58oOERG1PbKf30w9j0F6WlX4MprCbuSyFxERUThwg3IUk91ArIeRFHb1spdvkFRTY13lZiIiIlkMdqJUaam43DRyJHD33eK+V6/QAwu9Kex2VW4mIiKSxWAnClm5kqI3hT1cvbGIiIiMYrATZaxeSdFbJNCuys1ERESyGOxEmXCspOgpEmhX5WYiIiJZzMaKMuFaSSkoAPLytFPJ1cteNTX+V5vUVHUremMRERHJYLATZcK5kiKTwq5e9rrjDhHY+KvcbFVvLCIiIhm8jBVl7OwyHoidvbGIiIi0cGUnykTqSorsZS8iIqJwY7AThdSVFH8Vi/X0wDJbKJWbiYiIrMJgJ0pxJYWIiEgOg50oxpUUIiIibdygTERERDGNwQ4RERHFNAY7REREFNO4Z4cCcrn0bYDWO56IiCgcGOyQX6Wl/lPbX3jBf2q73vFEREThwstYMcjlArZtA954Q9zr7YBeWiqKFvo2HK2pEY+XloY2noiIKJwciuKvfWPbUl9fj7S0NNTV1aFjx452Tyckoa6wuFxAr16BO6urjT2rqsQlKr3jiYiIzCL7+c2VnRhixgrLjh2BAxdAtKeorhbjjIwnIiIKNwY7McLlEis6/tbp1MeKirQvaR05Inc+dZze8UREROHGYCdGmLXC0qOH3PnUcXrHExERhRuDnRhh1grLsGFij43aQd2XwwHk5IhxRsYTERGFG4OdGGHWCovTKTYzA60DGPXr3/62ZbOx3vFEREThxmAnRpi5wlJQALz1FnDRRd6PZ2eLx32zuvSOJyIiCiemniN2Us/VbCzAe6OyGgDpDTxYQZmIiCKZ7Oc3gx3ETrAD+K+zk5MjLiVxhYWIiGJJVNTZ+eijjzBu3DhkZWXB4XBg/fr1Xs8rioK5c+ciKysLSUlJGDFiBPbv3+81prGxEYWFhejatStSUlIwfvx4fBMsLSnGFRQAhw8DZWVASYm4r6pioENERG2XrcHO999/jyuvvBLLli3z+/zChQuxePFiLFu2DOXl5cjMzMRNN92E06dPu8cUFRVh3bp1WLNmDXbu3ImGhgaMHTsWLr09EmKI0wmMGAFMnCjueSmJiIjasoi5jOVwOLBu3Trk5+cDEKs6WVlZKCoqwiOPPAJArOJkZGTgueeew4MPPoi6ujp069YNq1evxl133QUA+Pbbb5GTk4P33nsPN998s99zNTY2orGx0f11fX09cnJyYuIyFhERUVsRFZexgqmqqkJtbS3GjBnjfiwxMRHDhw/Hrl27AAAVFRU4f/6815isrCzk5ua6x/izYMECpKWluW85OTnWvREiIiKyVcQGO7W1tQCAjIwMr8czMjLcz9XW1iIhIQGdO3cOOMafRx99FHV1de5bdXW1ybMnIiKiSNHO7glocfgUjlEUpdVjvrTGJCYmIjEx0ZT5ERERUWSL2JWdzMxMAGi1QnPs2DH3ak9mZiaamppw8uTJgGOIiIiobYvYYKd3797IzMzEli1b3I81NTVh+/btGDp0KABg0KBBiI+P9xpz5MgR7Nu3zz2GiIiI2jZbL2M1NDTgiy++cH9dVVWFvXv3okuXLrj44otRVFSE+fPno1+/fujXrx/mz5+P5ORk3H333QCAtLQ0TJ48GbNmzUJ6ejq6dOmC2bNnY8CAARg9erRdb4uIiIgiiK3Bzu7duzFy5Ej31zNnzgQATJo0CatWrUJxcTHOnj2LKVOm4OTJk7jmmmuwefNmpKamul+zZMkStGvXDnfeeSfOnj2LUaNGYdWqVXCyuAwREREhgurs2CmW2kUQERG1FbKf3xGfjRUOarxXX19v80yIiIhIlvq5rbVuw2AHcLefYHFBIiKi6HP69GmkpaUFfJ6XsQA0Nzfj22+/RWpqqmYNHz3UNhTV1dVt5vIY3zPfc6zie+Z7jlXR/J4VRcHp06eRlZWFuLjACeZc2QEQFxeH7Oxsy47fsWPHqPsFChXfc9vA99w28D23DdH6noOt6Kgits4OERERkRkY7BAREVFMY7BjocTERDz11FNtqg8X33PbwPfcNvA9tw1t4T1zgzIRERHFNK7sEBERUUxjsENEREQxjcEOERERxTQGO0RERBTTGOxY5KOPPsK4ceOQlZUFh8OB9evX2z0lSy1YsABDhgxBamoqunfvjvz8fBw4cMDuaVlqxYoVGDhwoLsQ13XXXYf333/f7mmFzYIFC+BwOFBUVGT3VCw1d+5cOBwOr1tmZqbd07JcTU0Nfv7znyM9PR3Jycm46qqrUFFRYfe0LNOrV69WP2eHw4GpU6faPTXLXLhwAU888QR69+6NpKQkXHLJJXj66afR3Nxs99RMxwrKFvn+++9x5ZVX4v7778ftt99u93Qst337dkydOhVDhgzBhQsX8Pjjj2PMmDH47LPPkJKSYvf0LJGdnY1nn30Wffv2BQC8+uqryMvLw9///ndcccUVNs/OWuXl5Xj55ZcxcOBAu6cSFldccQW2bt3q/trpdNo4G+udPHkS119/PUaOHIn3338f3bt3x6FDh9CpUye7p2aZ8vJyuFwu99f79u3DTTfdhJ/+9Kc2zspazz33HF588UW8+uqruOKKK7B7927cf//9SEtLw/Tp0+2enqkY7Fjk1ltvxa233mr3NMJm06ZNXl+vXLkS3bt3R0VFBW644QabZmWtcePGeX39zDPPYMWKFfjrX/8a08FOQ0MD7rnnHvzP//wP5s2bZ/d0wqJdu3ZtYjVH9dxzzyEnJwcrV650P9arVy/7JhQG3bp18/r62WefRZ8+fTB8+HCbZmS9jz/+GHl5ebjtttsAiJ/xG2+8gd27d9s8M/PxMhZZoq6uDgDQpUsXm2cSHi6XC2vWrMH333+P6667zu7pWGrq1Km47bbbMHr0aLunEjYHDx5EVlYWevfujZ/97Gf48ssv7Z6SpTZu3IjBgwfjpz/9Kbp3746rr74a//M//2P3tMKmqakJr7/+Oh544AFTm0NHmh//+Mf48MMP8fnnnwMA/vGPf2Dnzp34yU9+YvPMzMeVHTKdoiiYOXMmfvzjHyM3N9fu6ViqsrIS1113Hc6dO4cOHTpg3bp1uPzyy+2elmXWrFmDPXv2oLy83O6phM0111yD1157Df3798fRo0cxb948DB06FPv370d6errd07PEl19+iRUrVmDmzJl47LHH8Mknn+Dhhx9GYmIi/u3f/s3u6Vlu/fr1OHXqFO677z67p2KpRx55BHV1dbjsssvgdDrhcrnwzDPPYOLEiXZPzXQMdsh006ZNw6effoqdO3faPRXLXXrppdi7dy9OnTqFtWvXYtKkSdi+fXtMBjzV1dWYPn06Nm/ejPbt29s9nbDxvBw9YMAAXHfddejTpw9effVVzJw508aZWae5uRmDBw/G/PnzAQBXX3019u/fjxUrVrSJYOf3v/89br31VmRlZdk9FUu9+eabeP3111FSUoIrrrgCe/fuRVFREbKysjBp0iS7p2cqBjtkqsLCQmzcuBEfffQRsrOz7Z6O5RISEtwblAcPHozy8nK88MILeOmll2yemfkqKipw7NgxDBo0yP2Yy+XCRx99hGXLlqGxsTHmN+4CQEpKCgYMGICDBw/aPRXL9OjRo1XA/oMf/ABr1661aUbh89VXX2Hr1q0oLS21eyqWmzNnDv7jP/4DP/vZzwCIYP6rr77CggULGOwQ+aMoCgoLC7Fu3Tps27YNvXv3tntKtlAUBY2NjXZPwxKjRo1CZWWl12P3338/LrvsMjzyyCNtItABgMbGRvzf//0fhg0bZvdULHP99de3Kh3x+eefo2fPnjbNKHzU5Ap1024sO3PmDOLivLfuOp1Opp6TvIaGBnzxxRfur6uqqrB371506dIFF198sY0zs8bUqVNRUlKCDRs2IDU1FbW1tQCAtLQ0JCUl2Tw7azz22GO49dZbkZOTg9OnT2PNmjXYtm1bq8y0WJGamtpqD1ZKSgrS09Njem/W7NmzMW7cOFx88cU4duwY5s2bh/r6+pj7y9fTjBkzMHToUMyfPx933nknPvnkE7z88st4+eWX7Z6apZqbm7Fy5UpMmjQJ7drF/sfjuHHj8Mwzz+Diiy/GFVdcgb///e9YvHgxHnjgAbunZj6FLFFWVqYAaHWbNGmS3VOzhL/3CkBZuXKl3VOzzAMPPKD07NlTSUhIULp166aMGjVK2bx5s93TCqvhw4cr06dPt3salrrrrruUHj16KPHx8UpWVpZSUFCg7N+/3+5pWe7tt99WcnNzlcTEROWyyy5TXn75ZbunZLkPPvhAAaAcOHDA7qmERX19vTJ9+nTl4osvVtq3b69ccsklyuOPP640NjbaPTXTORRFUewJs4iIiIisxzo7REREFNMY7BAREVFMY7BDREREMY3BDhEREcU0BjtEREQU0xjsEBERUUxjsENEREQxjcEOERERxTQGO0QUdVatWoVOnTrZOocRI0agqKjI1jkQkRxWUCYi09x333149dVXWz1+8803m9oz7OzZszh9+jS6d+9u2jH1OnHiBOLj45GammrbHIhITux3OiOisLrllluwcuVKr8cSExNNPUdSUpLtDWa7dOli6/mJSB4vYxGRqRITE5GZmel169y5s/t5h8OBV155BRMmTEBycjL69euHjRs3eh1j48aN6NevH5KSkjBy5Ei8+uqrcDgcOHXqFIDWl7Hmzp2Lq666CqtXr0avXr2QlpaGn/3sZzh9+rR7jKIoWLhwIS655BIkJSXhyiuvxFtvvRX0vSxfvhz9+vVD+/btkZGRgTvuuMP9nOdlrG3btsHhcLS63Xfffe7xb7/9NgYNGoT27dvjkksuwW9+8xtcuHBB53eXiIxgsENEYfeb3/wGd955Jz799FP85Cc/wT333IMTJ04AAA4fPow77rgD+fn52Lt3Lx588EE8/vjjmsc8dOgQ1q9fj3feeQfvvPMOtm/fjmeffdb9/BNPPIGVK1dixYoV2L9/P2bMmIGf//zn2L59u9/j7d69Gw8//DCefvppHDhwAJs2bcINN9zgd+zQoUNx5MgR9+3Pf/4z2rdv7x7/wQcf4Oc//zkefvhhfPbZZ3jppZewatUqPPPMM3q/dURkhK0914kopkyaNElxOp1KSkqK1+3pp592jwGgPPHEE+6vGxoaFIfDobz//vuKoijKI488ouTm5nod9/HHH1cAKCdPnlQURVFWrlyppKWluZ9/6qmnlOTkZKW+vt792Jw5c5RrrrnGfY727dsru3bt8jru5MmTlYkTJ/p9L2vXrlU6duzodUxPw4cPV6ZPn97q8X/+859Knz59lClTprgfGzZsmDJ//nyvcatXr1Z69Ojh99hEZC7u2SEiU40cORIrVqzwesx3f8vAgQPd/05JSUFqaiqOHTsGADhw4ACGDBniNf5HP/qR5nl79erltVm4R48e7mN+9tlnOHfuHG666Sav1zQ1NeHqq6/2e7ybbroJPXv2xCWXXIJbbrkFt9xyi/vSWyDnz5/H7bffjosvvhgvvPCC+/GKigqUl5d7reS4XC6cO3cOZ86cCXpMIgodgx0iMlVKSgr69u0bdEx8fLzX1w6HA83NzQDE3hqHw+H1vCKRNBrsmOr9u+++i4suushrXKDN06mpqdizZw+2bduGzZs348knn8TcuXNRXl4eMO39V7/6Fb7++muUl5ejXbuW/702NzfjN7/5DQoKClq9pn379prvjYhCw2CHiCLKZZddhvfee8/rsd27d4d0zMsvvxyJiYn4+uuvMXz4cOnXtWvXDqNHj8bo0aPx1FNPoVOnTvjzn//sN2hZvHgx3nzzTXz88cdIT0/3eu6HP/whDhw4oBkEEpE1GOwQkakaGxtRW1vr9Vi7du3QtWtXqdc/+OCDWLx4MR555BFMnjwZe/fuxapVqwCg1YqPrNTUVMyePRszZsxAc3MzfvzjH6O+vh67du1Chw4dMGnSpFaveeedd/Dll1/ihhtuQOfOnfHee++hubkZl156aauxW7duRXFxMX73u9+ha9eu7veflJSEtLQ0PPnkkxg7dixycnLw05/+FHFxcfj0009RWVmJefPmGXpPRCSP2VhEZKpNmzahR48eXrcf//jH0q/v3bs33nrrLZSWlmLgwIFYsWKFOxsrlHo9//mf/4knn3wSCxYswA9+8APcfPPNePvtt9G7d2+/4zt16oTS0lLceOON+MEPfoAXX3wRb7zxBq644opWY3fu3AmXy4WHHnrI631Pnz4dgCiq+M4772DLli0YMmQIrr32WixevBg9e/Y0/H6ISB4rKBNRxHvmmWfw4osvorq62u6pEFEU4mUsIoo4y5cvx5AhQ5Ceno6//OUvWLRoEaZNm2b3tIgoSjHYIaKIc/DgQcybNw8nTpzAxRdfjFmzZuHRRx+1e1pEFKV4GYuIiIhiGjcoExERUUxjsENEREQxjcEOERERxTQGO0RERBTTGOwQERFRTGOwQ0RERDGNwQ4RERHFNAY7REREFNP+Pxy2FLzprd3bAAAAAElFTkSuQmCC\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.scatter(train.ENGINESIZE, train.CO2EMISSIONS, color='blue')\n",
"plt.xlabel(\"Engine size\")\n",
"plt.ylabel(\"Emission\")\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Modeling\n",
"Using sklearn package to model data.\n"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Coefficients: [[38.59777163]]\n",
"Intercept: [127.29727605]\n"
]
}
],
"source": [
"from sklearn import linear_model\n",
"regr = linear_model.LinearRegression()\n",
"train_x = np.asanyarray(train[['ENGINESIZE']])\n",
"train_y = np.asanyarray(train[['CO2EMISSIONS']])\n",
"regr.fit(train_x, train_y)\n",
"# The coefficients\n",
"print ('Coefficients: ', regr.coef_)\n",
"print ('Intercept: ',regr.intercept_)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"As mentioned before, __Coefficient__ and __Intercept__ in the simple linear regression, are the parameters of the fit line. \n",
"Given that it is a simple linear regression, with only 2 parameters, and knowing that the parameters are the intercept and slope of the line, sklearn can estimate them directly from our data. \n",
"Notice that all of the data must be available to traverse and calculate the parameters.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Plot outputs\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can plot the fit line over the data:\n"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0, 0.5, 'Emission')"
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.scatter(train.ENGINESIZE, train.CO2EMISSIONS, color='blue')\n",
"plt.plot(train_x, regr.coef_[0][0]*train_x + regr.intercept_[0], '-r')\n",
"plt.xlabel(\"Engine size\")\n",
"plt.ylabel(\"Emission\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Evaluation\n",
"We compare the actual values and predicted values to calculate the accuracy of a regression model. Evaluation metrics provide a key role in the development of a model, as it provides insight to areas that require improvement.\n",
"\n",
"There are different model evaluation metrics, lets use MSE here to calculate the accuracy of our model based on the test set: \n",
"* Mean Absolute Error: It is the mean of the absolute value of the errors. This is the easiest of the metrics to understand since it’s just average error.\n",
"\n",
"* Mean Squared Error (MSE): Mean Squared Error (MSE) is the mean of the squared error. It’s more popular than Mean Absolute Error because the focus is geared more towards large errors. This is due to the squared term exponentially increasing larger errors in comparison to smaller ones.\n",
"\n",
"* Root Mean Squared Error (RMSE). \n",
"\n",
"* R-squared is not an error, but rather a popular metric to measure the performance of your regression model. It represents how close the data points are to the fitted regression line. The higher the R-squared value, the better the model fits your data. The best possible score is 1.0 and it can be negative (because the model can be arbitrarily worse).\n"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Mean absolute error: 22.59\n",
"Residual sum of squares (MSE): 897.10\n",
"R2-score: 0.78\n"
]
}
],
"source": [
"from sklearn.metrics import r2_score\n",
"\n",
"test_x = np.asanyarray(test[['ENGINESIZE']])\n",
"test_y = np.asanyarray(test[['CO2EMISSIONS']])\n",
"test_y_ = regr.predict(test_x)\n",
"\n",
"print(\"Mean absolute error: %.2f\" % np.mean(np.absolute(test_y_ - test_y)))\n",
"print(\"Residual sum of squares (MSE): %.2f\" % np.mean((test_y_ - test_y) ** 2))\n",
"print(\"R2-score: %.2f\" % r2_score(test_y , test_y_) )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Exercise\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Lets see what the evaluation metrics are if we trained a regression model using the `FUELCONSUMPTION_COMB` feature.\n",
"\n",
"Start by selecting `FUELCONSUMPTION_COMB` as the train_x data from the `train` dataframe, then select `FUELCONSUMPTION_COMB` as the test_x data from the `test` dataframe\n"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [],
"source": [
"train_x = train[[\"FUELCONSUMPTION_COMB\"]]\n",
"\n",
"test_x = test[[\"FUELCONSUMPTION_COMB\"]]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Click here for the solution\n",
"\n",
"```python \n",
"train_x = train[[\"FUELCONSUMPTION_COMB\"]]\n",
"\n",
"test_x = test[[\"FUELCONSUMPTION_COMB\"]]\n",
"\n",
"```\n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now train a Linear Regression Model using the `train_x` you created and the `train_y` created previously\n"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None,\n",
" normalize=False)"
]
},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"regr = linear_model.LinearRegression()\n",
"\n",
"regr.fit(train_x, train_y)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Click here for the solution\n",
"\n",
"```python \n",
"regr = linear_model.LinearRegression()\n",
"\n",
"regr.fit(train_x, train_y)\n",
"\n",
"```\n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Find the predictions using the model's `predict` function and the `test_x` data\n"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [],
"source": [
"predictions = regr.predict(test_x)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Click here for the solution\n",
"\n",
"```python \n",
"predictions = regr.predict(test_x)\n",
"\n",
"```\n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Finally use the `predictions` and the `test_y` data and find the Mean Absolute Error value using the `np.absolute` and `np.mean` function like done previously\n"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Mean Absolute Error: 20.61\n"
]
}
],
"source": [
"\n",
"print(\"Mean Absolute Error: %.2f\" % np.mean(np.absolute(predictions - test_y)))\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Click here for the solution\n",
"\n",
"```python \n",
"print(\"Mean Absolute Error: %.2f\" % np.mean(np.absolute(predictions - test_y)))\n",
"\n",
"```\n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can see that the MAE is much worse when we train using `ENGINESIZE` than `FUELCONSUMPTION_COMB`\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Thank you for completing this lab!\n",
"\n",
"\n",
"## Author\n",
"\n",
"Saeed Aghabozorgi\n",
"\n",
"\n",
"### Other Contributors\n",
"\n",
"Joseph Santarcangelo\n",
"\n",
"Azim Hirjani\n",
"\n",
"##