diff --git a/Term Project(Resampling.ver).ipynb b/Term Project(Resampling.ver).ipynb index cba30be3705da8471e630ae640df95aba3cdb26e..9e5f471ace79320c81b9e65c294d34e9328c7142 100644 --- a/Term Project(Resampling.ver).ipynb +++ b/Term Project(Resampling.ver).ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 70, "metadata": {}, "outputs": [], "source": [ @@ -17,11 +17,12 @@ "\n", "from imblearn.over_sampling import RandomOverSampler\n", "from sklearn.metrics import classification_report, confusion_matrix\n", - "\n", + "import sklearn.metrics as metrics\n", "\n", "#데이터 로드\n", "por = pd.read_csv(\"./student-por.csv\")\n", "math = pd.read_csv(\"./student-mat.csv\")\n", + "#my = pd.read_csv(\"./my_data.csv\")\n", "\n", "data = pd.concat([por, math], ignore_index=True)\n", "\n", @@ -30,8 +31,6 @@ "data = pd.concat([X,Y],axis=1)\n", "\n", "\n", - "\n", - "\n", "\n" ] }, @@ -100,6 +99,7 @@ "data[\"Grade\"] = data['G1']+data['G2']+data['G3']\n", "data = data.drop(columns=['G1','G2','G3'])\n", "print(data.info())\n", + "\n", "data.shape" ] }, @@ -839,14 +839,29 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 74, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "0.9078726968174204\n", + "accuracy 0.8927973199329984\n", + "precision 0.8937631783498577\n", + "recall 0.8929638784714978\n", + "f1 0.8931829478653762\n", + " precision recall f1-score support\n", + "\n", + " 1 0.77 0.80 0.78 124\n", + " 2 0.85 0.81 0.83 120\n", + " 3 0.91 0.90 0.90 109\n", + " 4 0.95 0.96 0.96 122\n", + " 5 0.99 1.00 1.00 122\n", + "\n", + " accuracy 0.89 597\n", + " macro avg 0.89 0.89 0.89 597\n", + "weighted avg 0.89 0.89 0.89 597\n", + "\n", "Confusion Matrix\n" ] }, @@ -856,20 +871,18 @@ "<AxesSubplot:xlabel='Predicted', ylabel='Actual'>" ] }, - "execution_count": 9, + "execution_count": 74, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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LPGeM2YMz7mkksBOY6e/gqiSJiIhIgWSt3QdcBdTBmdY/HBhkrZ2cZbdngInABGA5ztDxjtbaZPxQJUlERET8yg+3JbHW3uejbTVw+Slek4qzuOSg0z2fkiQRERHxKx/kSEGn7jYRERERH1RJEhEREb/yQ3dbsClJEhEREb/CMEdSd5uIiIiIL6okiYiIiF8REeFXSlIlKUiWL13Ede2aZ2uz636jw2WNT3qMf22US1HmH+3Pr8CvL3TMs+Nf1agC8x9ryR8vXcMXA1vS9rxzsm2P8ECP1rVY+Hgrfn+xIwseb0W3FjXzLJ6CaObHH9Hlmqto1rQx99zZlbU//eh2SCFH1zg4dJ1zx+MJ3KOgUJIUBL/9/BMvDHmC9PT0bO2bN66nSEwMYyZOy/a48ba7XIo0f2haszSv3tMkz36QLqtblnH/uoiVG/+izzurWbfrCON7XMyFNUpl7vPQ1fUY2Lk+n67eSc+3f2Duj7t55saG9Gl7bt4EVcDMmfUZzw4bTKcu1/Hy6NcpXrw4/Xr3YMeO7W6HFjJ0jYND11lORUlSHkpOTubD6ZP4vwd6EBkZedL2Pzeup2btOjQ8/4Jsj3MqVnIhWvcVioygT9tzef/B5qSmpvt/wSk0r1OWLWM6U7VMzEnbBnSsxzJ7gCEzf+PbP/bz8PSfWLP5EP071AGcTzk92tRi/DebeGPBRpav/4vR89czY/k2erWtfVZxhYL09HTGjX2Nm2+9jb79H6BFy1aMGfsmpUqXZvrUKW6HFxJ0jYND1/n05NN7t+WpoI5JMsa0BnoAZYDPgQnelTAztpcGZllrWwYzrrzyw4plfDD1HXo98DBHDsfx3/enZtu+edN6atep51J0+U/rhuXp3+Fcnp+1jtKxhejZJntCEhnh4aGr63LLpdUoV6wQdnc8I+esY/n6v3J9jsLRETStVZqhM7Pf/HnBr3t55FpDhAeKFYnmk1U7+XLtnmz7/LkvgXLFCxNTKJKk5FTC1bZtW9m1ayet27TNbIuOjqZFy9Z8t2ypi5GFDl3j4NB1Pj0FKLcJmKBVkowxXYCFQCWgEDAW+NYYUyrLboWAK4IVU14zDc5j2swvuPG2u3xmzps3bWT/3j306XYr17Royr23dOKrubNciDR/WLvtMC2GfcPkJVtI91FIGnl7Y3q1qc27326m99ur2bQvgcl9LqVpzdKZ+0RGeIiM8BDh/c6O8Hgy2wCqly1KdGQEWw4kZjv29r+OElMoksqlYziSlMLgmb/y284j2fZpd34Fdh1KCusECWDrli0AVKteI1t71arV2LF9G6mp4X19AkHXODh0ncWfYFaSngaettY+D2CMaQ58AiwwxrS21iae8tUFULlzKvzjtgP793E47hA7t2+je79/U7x4CRYt+IKXnn0aj8dDh2uvC2Kk+cPew8f+cdu558Ry66XVeOz9tXy40hkr8O0f+zmnRBEe7WS4842V3NKsKqPuapLtdUue+fsT4u2vryD5hPNLL/HYiWz7JXifFyvi+0eia/NqtDDlGfzfX0/7fYWaxIQEAGKLxmZrj42NJS0tjaSkJIoVK+ZGaCFD1zg4dJ1PT0HqJguUYCZJDYDbM55Ya1caY9oBS4H/GmM6BzEW1xUrXpznXn2T2nXqUbZceQCaNmvOXwf2MW3SW2GZJJ1K87plAVj0+77MqlDG84Gd6xMd6WHhr3vpMsopkTeqVpLnujamx4RV7DtyHHC6y0ylEgDkLFRl/Oyn+ahgXX9RFUbc1oi5P+5iytItAX1fBVHGBIScvzAz2iPC8BdpoOkaB4eu8+lRkpS3DgA1gD8zGqy164wxNwFfAe9wBnfoLaiKFInhkuYn9yxe3PwKflj5HUlHjxJTtKgLkeVPpYoWAmDV8A4+t5eOLcS+I8eJO3oYgNjCzre23R3PjoNJmfvFH0vJtj1DxvP4pJRs7T1a1+LJ6xuy8Ne9DJimacHgJPgAiYmJlC1XLrP96NGjRERE6Ps2AHSNg0PXWfwJZpL0GfCWMebfwNKM7jVr7RJjTA9gKlAliPG4ase2Lfy4ehVXd76BQoUKZbYnHz9O4cJFKBJz8qyscBZ/7ARpaencMuY7UnzMfDuUmJyr42z76yipaelUL1uU77K0VytblIRjJ7J1+f1fZ8P9Heoyc9V2Br7/M6m+ykxhqHoNZ/zGjh3bM/+d8bxmzVph+Wkz0HSNg0PX+fSE4+UI5hIATwO/AnPJMTjbWvsecA9wWRDjcdWB/ft47aVnWbX87xkU6enpLFv8Nec3aaofzhxW/3mQiAgPsYWj+GX74czHlaYcPVrX5kQuE5jjKWn8b/NBrmpcMVt7h/MrsHLjX5ndbf9qVYv7O9Rl0uI/eeS9tUqQsqhRoyYVK1Zi0dcLM9tSUlJYumQxzZqHzY9wntI1Dg5d59OjJQDykLU2AbjZGFMBOGmQtrV2hjHmW+CmYMXkpkZNLuL8Cy5kzIvDSYg/Qply5Zj72X/5c9N6Xn1L63Pk9PvOI8z7aTev3nMho+evZ9OeBJrXLcsDV9Vl/NebTpoNt3LjX9T89+c+jzVu4SYm92nGc10b8dXPe7juoio0rVWarq8tB6B8icIM6lKfdbuOMGfNrmyLTAL8vP1wWCdNHo+H7j178fyI4ZQoWZImFzblgxnTiTt0iHu63ed2eCFB1zg4dJ3Fn6Dfu81au/cU23YCrwcxHNdERkYy9IXXmPTWa0yZ+AZHDh+mjmnAC2PGYxqc53Z4+dKAqT/y8LX16N++DmWLF2LnwSRemLOOCd/86f/FWSz+fR8Dpv3IQ1fX5eZLqvLnvkR6v72aNVviAGhVvzyFoyNpULkEnz585Umvv/CJLzmUmHJSezjpesddHDt+nBnTpjJ96mRM/Qa8OeEdqlar5nZoIUPXODh0nXOvABWAAsaT81YZBdW2g8dD443kUy2HLnA7hLDwx8thNclTRM5CkSiCmrZcNHxRwP7O/u/pNgUi5dJtSURERER8CHp3m4iIiBQ84djdpiRJRERE/CpIs9ICRd1tIiIiIj6okiQiIiJ+hWEhSUmSiIiI+KfuNhEREREBVEkSERGRXAjDQpKSJBEREfFP3W0iIiIiAqiSJCIiIrkQhoUkJUkiIiLin7rbRERERARQJUlERERyIQwLSUqSRERExD91t4mIiIgIoEqSiIiI5EI4VpKUJImIiIhfYZgjqbtNRERExBdVkkRERMQvdbeJiIiI+BCGOZKSJBEREfEvHCtJGpMkIiIi4oMqSSIiIuJXGBaSlCSJiIiIfxFhmCWpu01ERETEB1WSRERExC+3CknGmELAUOAuoDTwE/CYtXa5d3sTYDRwCfAX8Jq1dlQgzq1KkoiIiPjl8XgC9jhNg4HuQC+gKfAHMN8YU8UYUw5YCGwALgaeBoYZY3oF4j2rkiQiIiL52fXAdGvtlwDGmEeAnsAVQB0gGehnrT0BrDPG1AEGARPP9sSqJImIiIhfEZ7APU7TPqCzMaamMSYSJ0E6DvwItACWehOkDIuB2saYKmf7nlVJEhEREb8CuZikMaYUUMrHpjhrbVyOtgeBj4DNQCqQBtxqrd3gTYR+z7H/Lu/XasDOs4kzZJKkYoVD5q3kS2ueu4bUtHS3wwh5lw7/2u0QQt6KJ9u6HUJYiDiDcoGElQE4Y41yGgoMydF2PnAEuAEn6ekJTDPGtAaK4lSVssp4XuRsg1RmIbmiBElEcksJUmgK8Oy20cBkH+1xWZ8YY6oD04CrrbWLvM2rjTHnAcOAJKBwjmNkPE842yCVJImIiIhfHgKXJXm71OJysWszIBr4IUf7SuA6YBNQOce2jOc7zjxChwZui4iISH6Vkeg0ztHeGFgPLAGuNMZkLfq0AdZba/ec7clVSRIRERG/XOpFXQUsAyYZY/rhJE3dgPY4M9s2AgO920cCFwEPA/0DcXJVkkRERMQvNxaTtNam4XSrfY0zhmkN0A5ob61dbq3dB1yFs17SGmA4MMhaOzkQ71mVJBEREcm3rLWHgPu9D1/bVwOX58W5lSSJiIiIX27du81NSpJERETEr4gwzJI0JklERETEB1WSRERExK8wLCQpSRIRERH/AnnvtoJC3W0iIiIiPqiSJCIiIn6FYSFJSZKIiIj4p9ltIiIiIgKokiQiIiK5EH51JCVJIiIikgvhOLvtH5MkY8yS0zhOurW2VQDiEREREckXTlVJSgPSgxWIiIiI5F8R4VdI+uckyVrbOohxiIiISD4Wjt1tAZndZow5PxDHEREREckvcjVw2xhTFngeaA0U5u9B7hFALFACiMyD+ERERCQfCMNCUq4rSa8A/wL+AI4DfwErcJKl4kCvPIlORERE8gWPxxOwR0GR2ySpIzDMWnsd8Caw3VrbFagP/Ao0yqP4RERERFyR2ySpNLDc++9fgYsBrLXxOFWmToEPTURERPKLCE/gHgVFbpOk/UAp7783ABW845QAdgJVAhyXiIiI5CPqbvtnXwNPGGPqWGu34CRN93q3dQEO5EFsIiIiIq7JbZL0NFAWmOx9/jwwyhhzGHgQmBT40ERERCS/8ATwUVDkagkAa+1WY0x9wHifjzHG7AeuAL631k7NwxhFRETEZREFqJssUHJ9g1tr7TFgbZbnM4AZeRGUiIiIiNtyu5jkM/72sdYOO/twREREJD8Kw0JSritJQ06xLR7YCyhJ8mPN6lXc3/u+f9z+yecLqFRZEwXP1tGjibz1+qss+vorjh1LolHjJvR76BHq1qvvdmgFVkyhSAa0P5cO51WgSHQEa7cf5tWvNrJ+bwIAxQpH8lD7OrRtUJ6ihSJZtfkQo+ZvYMehJJcjL7hSU1OZMX0qn878mN17dlOpUmVu63oHXe+4q0DNDioIZn78EZMnvc3evXsw9Rvw6MBBXNDkQrfDynfC8fsut0lStI+2EkAbYAzQI2ARhTBTvyETJ7+frS05+ThPDByAqd+QChUruRRZaHlq4AB+Wfsj/+p9P3Xq1uOrLz7n/l7deHvKh1SvWcvt8AqkV7o2okm1kry5eDMb9iZwbeOKvNv9Iu6c8ANb/zrK87ecT/2KxRn91UbiklLo3aoW7/yrKTe9sZLE46luh18gTRw/jnffmUivPv1p1PgCflyzmlEvPs+xY8e4r3tPt8MLGXNmfcazwwbTp9/9nHd+I95/bxr9evfgo09mUbVqNbfDE5flduC2r99yh4BPjDEVgFHApYEMLBTFFivG+Y0vyNb26kvP48HDkBEvEhERkPsNh7U/1v3GqpXLefTxwdxw820ANGt+BX2738XEt15n+MhXXI6w4GlQqTiX1ynL8Dl/8N/VOwFYsekg1XtcxP1ta/PW4s20rFeOhz/4ma/X7Qdg075E5j98Ba1Neeb+vMfN8AuktLQ0pk+dTLf7etCzd18ALm1+GYcOHmLqlElKkgIkPT2dcWNf4+Zbb6Nv/wcAaH7Z5VzfuSPTp05h0BNPuRxh/hKGhaTcD9w+hQ3k8rYkxpii3n1/sdYeNcZcCDyEsxjl78Cr1tqtAYipQNj850ZmfjSDRx57itKly7gdTkjYvnULAJdedkW29kYXXMjsTz52IaKCr0bZogAs3/hXtvafth/m5ouq8NSnv3P3hB+w3q43gJTUNAAKRYXhb9UASIiPp3OX62nXvkO29hq1anLo4EGSjh4lpmhRl6ILHdu2bWXXrp20btM2sy06OpoWLVvz3bKlLkaWP4Xj7LazKl0YY4oAfYHdudi3IbAJ58a4fxhj2gPLgGZAHNAZ+NG7X1h4640xVKteg+tvutXtUELGORUrArB3T/Zvyd07d5CYmMCRw3EuRFWw7T1yDICKJYtka69SKobiRaIoEh3BLzuPkHwijcgID7XLxzL0hgYciD/ON97KkpyeEiVLMujJZ6jfIPuvwyWLF1OhQkUlSAGydcsWAKpVr5GtvWrVauzYvo3UVHUVh7vczm7bDqTnaI7EWWCyEPDvXBzmRZykaDjwf8Bs4H2gp7U23RgTBUwDXgauyVX0BdiunTtY9u0iHntqqLrZAqhBw0ZUq16Tl0cO58khI6hSrTpffzWfFd85nwqTkpIoUbKUu0EWML/uPMKWA4k82cnw9Ge/s/1gElefX4Er6zp3JoqJjuRI0gkABl9Xn+svrExqWjqDP/udw952OXufzPyY71cuZ+CgJ90OJWQkJjjVz9iisdnaY2NjSUtLIykpiWLFirkRWr4UhoWk07otSc7Hl8BbQHtr7eu5OEYr4Clr7c/Ao0AR4A1rbTqAtfYEMAJocVrvoICa9cnHFC9Rgo7XdnE7lJBSqFAhRrw0hojICHp268o1bS5j/txZ3NmtOwBFisS4HGHBk5KazsMf/EJqejrv92nGssdb0eWCikz+zukZP5by96ftj37YSc931/DBqh08e9N53NhUkxECYd7nc3hu+BDad7ia2++82+1wQkZ6uvPZP+esrYz2cOxeOpVwvHdbbgdu33eq7caYKG+ScyrHgBjv8fYaY6YAOecHlwQO5yamgm7J4q9p2bodhQoVcjuUkFP73DpMef9T9u7ZTWpqKpWrVGXShHFEREQQq0+FZ2TT/kRue3MVFUoUJirCw864Y/RpXYvUtHQSssxe+3XnEQB+2HKICiUK06NFTT5d47c3Xk5h+tTJvDLqBVq1bstzL7xUoP7A5HfFihcHIDExkbLlymW2Hz16lIiICHVrSu4qScaYP72DrH1tuwLIzfSVhcAYY0wdAGvtv6y167Ic53JgPDAnNzEVZHt272LL5j9p3ba926GEnGPHkpg/dzYH9u+jQsVKVK5SFYBNGyy1zq1DVFQg5iqElyLREXRuXJHyxQux98hxdsY5Y5TqVSjGxn0JVCxZmBsuPLli9MfueM4pXjjY4YaU18e8wssvjaRTl+t46ZUxREfrQ1UgVa/hjEXasWN7tvYdO7ZTs2YtJaQ5RATwUVD8418MY8xjQEZHbU3gIe/YpJya44xP8ucRYB7OopN35jjXHcB7wDfAY7k4VoH2+2+/AHDe+Rf42VNOV1RUFKOeH0bPvg9w+933Ac74rxXLl3L7Xfe6G1wBdSI1nae61OeNbzYxbYXzK6BKqSJcWbcsU5dvo0bZogy9oSE7Dx3jhy2HMl/X/NwybNiX6FbYBd6M6VOZ9PYE7ry7G48OfFx/sPNAjRo1qVixEou+XsjlV1wJQEpKCkuXLKZFy9buBpcPheP34Kk+VkcCGYtEpAO+/sKk4cxM87uYhLV2F9DEu65STotwkq0fMsYohbI/N26gVKnSlCxVyu1QQk5UVDSdb7iZqe9OoHSZssTGxvLm669SqlRput6pJOlMnEhL55M1u+jZshYHE1NIOH6CAR3qcCgxhekrtpFwPJW12w8z7MYGjP36Tw4dTebGppVpUq0k909f6/8EcpL9+/cx5tVR1K1bj6s7XssvP2e/jg3PO19V0QDweDx079mL50cMp0TJkjS5sCkfzJhO3KFD3NPtPrfDk3zgH3/KrLXPAc8BGGPSgBbW2u/O9oTW2r0+2vaQuy67kHDo0MHMvnAJvH4P/AePB8aNGcXx5GQuurgZ/f/9qJLSszBmwUbS09P5z1V1KBwVwarNh3jlqw2Zs9cefO8nHmpfhwEdzqVETDTrdsXTd+pP2SpLknsrvltGcnIyGzas5967bz9p+zdLVlC6dGkXIgs9Xe+4i2PHjzNj2lSmT52Mqd+ANye8Q9VqWm07p4jwKyThyRjFfyrGmBrALqCGtXajt60c0MBamy9W3DqYmBryFSg3pabp8gZD+1Hfuh1CyFvxZFv/O8lZiQjHv6YuKBJFUC/0w7P/CNgfgleuq18gvklyO34qEVgMzM/S1gz41hjzlTGmRKADExERkfwjHJcAyG2S9CJQA3ggS9t84CqgPvBsgOMSERERcVVuk6RrgMestZmVJGttmrV2IfAMcGNeBCciIiL5Q4QncI+CIrfTI4oBCf+w7QDO7UlEREQkRBWgXrKAyW0laQ3Q6x+29QB+Ckg0IiIiIvlEbitJI4B5xpifgU+AvUB54AbgAuDaPIlORERE8oVwvJddripJ1tqvgM4491p7GngDGIyzyGQXYGVeBSgiIiLuC8fbkuQ6VmvtfGvtpTi3KqkKlAB64wza3pE34YmIiIi440zXtb8K6AdcDHiAs16JW0RERPIvN3vbjDHdgEFAbWATMMRa+7F3WxNgNHAJ8BfwmrV2VCDOm+skyRhTD+iLcw+3UsA2nLFKU6y1mwIRjIiIiORPbo1JMsbcDUwCHgHmAl2BD4wxuwALLAQ+xSneNAPeNMYcttZOPNtznzJJMsZE4gzO7ge0AZKBed62u6y1y882ABERERFfjDEeYDjwurV2jLd5hDGmBdAWaIWTm/Sz1p4A1hlj6uBUnc46SfrHMUnGmKE41aKPgZLAQ0AlnEpS+A1xFxERCWMeT+Aep8EANYEZWRuttR2ttcOBFsBSb4KUYTFQ2xhT5azeMKeuJD0N/AzcYq1dkRmtMbFne1IREREpWAK5UrYxphTO0J2c4qy1cVme1/N+LWyMmYsz7mgz8Ky1dg5QBfg9xzF2eb9WA3aeTZynmt32Nk729q0x5mtjzL3GmKJnczIRERERYABOspPzMSDHfiW8X6cB/8WZOPYlMMsY0wEoChzP8ZqM50XONsh/rCRZa3sbY/4N3AZ0B94FXgdm46yPlH62JxcREZGCIcADt0cDk320x+V4nuz9+oq19l3vv38yxlwMPIqzfmPhHK/JeP5Pt1PLtVMO3LbWJgFTgCnegVA9gG44Y5LeN8a8D3xgrV17toGIiIhI/hXIHMnbpRaXi10z1mH8JUf7rziTyDYClXNsy3h+1ms4ns5ikhuttY/j9PF1AX4EHgbWGGN+O9tARERERHL4EYjHGYuUVSOcBGkJcKUxJmvRpw2w3lq752xPftqLSVpr03DWKZhrjCmPM9vtX2cbiIiIiORfgRy4nVvW2iRjzIvA0951kVYCtwNXAx1wKkwDgUnGmJHARTgFnP6BOP+ZrrgNgLV2PzDK+xAREZEQ5XFp9R9r7bPGmARgGM5t0f4AbrbWfg1gjLkKeA1YA+wBBllrJwfi3GeVJImIiIjkNWvtaJzB3r62rQYuz4vzKkkSERERv9zobnObkiQRERHxKxyTpFzPbhMREREJJ6okiYiIiF+ewC4mWSAoSRIRERG/1N0mIiIiIoAqSSIiIpILYdjbpiRJRERE/AvwDW4LBHW3iYiIiPigSpKIiIj4FY4Dt5UkiYiIiF9h2Num7jYRERERX0KmklQkWvleXkpLdzuC8LDyqXZuhxDyyjR7wO0QQt6hH8a6HYLkgQjCr5QUMkmSiIiI5B11t4mIiIgIoEqSiIiI5IJmt4mIiIj4oMUkRURERARQJUlERERyIQwLSUqSRERExD91t4mIiIgIoEqSiIiI5EIYFpKUJImIiIh/4dj1FI7vWURERMQvVZJERETEL08Y9rcpSRIRERG/wi9FUnebiIiIiE+qJImIiIhf4bhOkpIkERER8Sv8UiR1t4mIiIj4pEqSiIiI+BWGvW1KkkRERMS/cFwCQN1tIiIiIj6okiQiIiJ+hWNVRUmSiIiI+BWO3W1KkkRERMSv8EuRwrN6JiIiIuKXKkkiIiLil7rbRERERHwIx66ncHzPIiIiIn6pkiQiIiJ+qbtNRERExIfwS5HU3SYiIiLik5KkIEpNTWXalHe56bpruazZhdx0fSc+mDGd9PR0t0MLKSkpyYx7fTSdrm7LFc0upE+Pe1n3+29uhxWyFi/6msubXeh2GK7q1KoR+5aN8rtf+8sasGz6/3Fg+cv8MusZ+t3eKs9iqlqhFB++3Is9S15iy8LnGPHv64mOisy2T/MLajF/wkPsXvIif341greH38M5ZYrnWUz51cyPP6LLNVfRrGlj7rmzK2t/+tHtkPIljydwj4JCSVIQTRw/jrGvvcq1na9j9GvjuOrqjox68XmmvPuO26GFlJdfHMkHM6ZxX/dejBr9OkViitCn573s3rXT7dBCzk8/ruHJQf9HOOf5zS+oxaRnu/kdr3Fp41p8MqYvv23cza3/mcC7nyznhYdv4sG72gQ8pkLRUcwZ9wDVKpWhx9NTGTlxPn26tuTFR27K3MfUqsC8tx4k/uhx7n18Mo+/8imXXVCb2ePuJyoqfP40zJn1Gc8OG0ynLtfx8ujXKV68OP1692DHju1uh5bvROAJ2KOg0JikIElLS2P61Ml0u68HPXv3BeDS5pdx6OAhpk6ZxH3de7ocYWiIj4/n05kf8+CAh7m16x0AXNj0Ytq2bM7cz2fTs3c/lyMMDcnJybw3fQrjXh9DTExR0tJS3A4p6ApFR/HAna15pn8nEpOSKRRx6sTiwbva8Pufu+kzZDoAi763mFoV6XNbS15/b9EZxfDH3KFMm/09I8bPy9be9ZqLObdaeRp0HszOfXEAJB1P4fUnbuf5ifPZdzCevl1bsefAEe54dCInTqQBsHHbPpa9N5B2zevz5bLfzyimgiQ9PZ1xY1/j5ltvo2//BwBoftnlXN+5I9OnTmHQE0+5HKHkZIypB6wBBlhr3/a2NQFGA5cAfwGvWWv9l3ZzIXw+LrgsIT6ezl2up137Dtnaa9SqyaGDB0k6etSlyEJLTEwMU977kOtu+PsTc1RUFB48JCcnuxhZaFm2dAmT3p7Afx4ZyO133u12OK64+oqGPNr9Kp4Y/RlvfvCt3/0HvfIJ9z7+bra25JQTFC6U/bNq20vrs2Tqoxxc8Qob5w/n6X6diIg4vU/ebS81/PTH9swECWDOop+Jjo6kTTMDwLpNuxkz7ZvMBAlg/dZ9ANSsXO60zldQbdu2lV27dtK6TdvMtujoaFq0bM13y5a6GFn+5HZ3mzEmGngPiM3SVg5YCGwALgaeBoYZY3qd9RsmH1SSjDG/ANdaa0O6tlmiZEkGPfnMSe1LFi+mQoWKxBQt6kJUoScqKor6DRoCTvVu965djB/3Oh6Ph2s7dXE5utBx3vmNmDv/a0qUKMGbb7zudjiu+N9vW2nQaTCHE5J4ss+1fvffsTcu898li8XQqXUj7urcjJFvf5nZ3rpZPWaN7cenX//E8LfmUq9GBYY+2IUyJWP5z8iPAIiMzP7ZNiLCk9mWlpZOeno6dWucwwZvwpPh4OFEDscnUafGOQBM+PjkJKBTy/MBsFv25OIKFHxbt2wBoFr1Gtnaq1atxo7t20hNTSUyMtLHK8OTx/1usqFAfI623kAy0M9aewJYZ4ypAwwCJp7tCYOSJBljup9icx3gDmPMAQBr7aRgxJQffDLzY75fuZyBg550O5SQ9Pb4cYx/cywAfe9/iJq1arscUeioUKGC2yG4btf+w2f0uuqVSmPnDQecRGtilmRlyP1dWPXLFroNcipOC5av4+CRRCYOvYdXpyxk2+6DJKx+Ldvxnuh9DU/0vgaAabNX0nvwdIrHFiH+6PGTzp1w9BglihXxGVfVCqV47j838r/ftrJ41fozem8FTWJCAgCxRWOztcfGxpKWlkZSUhLFihVzIzTJwRjTEugDNAG2ZdnUAljqTZAyLAaeMsZUsdae1WDUYFWSxgAZpRJfqehI79d0ICySpHmfz+G54UNo3+HqsO2uyGtt2nXgokuasXrV90wcP46UlBT6P/Bvt8OSMHck4RhX9xpDxXIleKZfZxZPeYTmdzi/Ai8+rwZD3piTrVq0YPk6IiMjaHVJPabNXskVd72Yue2/o/swb8mvTPrkOwAOHHL+6Hs8Hp+zZj0eD2lpJ7dXrVCKeeMfIiLCwz2D3j1pe6jKuEY5B91ntEcUpGlYQRDIy2GMKQWU8rEpzlob52PfacCD1trtxpism6sAOQfQ7fJ+rQYUiCTpIpx+xMPAvVkzO2NMPHCBtfbPIMXiuulTJ/PKqBdo1botz73wUliuYhoMdes5P0gXXdyMxKOJTJv8Dr369Cc6OtrlyCScxcUnsWT1BgB+27ib1R8/wQ3tmvDtqvVERkYw/KHrGf7Q9Se9rmK5EgCs+f3vD9HJKSfYvf9wtjaAIwlJFC9a+KRjxMYU5nBCUra2hudWYtbY/kRFRdK531g27zhw1u+xoChW3FnuIDExkbLl/h6HdfToUSIiIjQMIocAz0obAAz20T4UGJKj7U1ghbV2ho/9iwI5y6YZz32XTU9DUJIka+16Y8xlwDDgJ2PMA9baD4Nx7vzm9TGvMOntCXS+7noGDx1BVJTrw8JCyoED+1m+bAntOlxNbOzfZfL69RuSnJzM4cNxlCtX3sUIJVx1ad2YXfvi+F+WhOa3jbtITjlBlXNKcSTxGADPT/yCzxf/ctLrd59G997GbfupVTX74OsyJWMpWTyGDVv2ZrZdcn4NPhvbn/jEY3Ts8Rqbtu0/3bdVoFWv4YxF2rFje+a/M57XrFlLH2Dz1mhgso/2uKxPjDH34HSpNfqH4yQBOT8RZDxPOOPovIL2F9rbX/iEMWY+MNUYcx3QP1jnzw9mTJ/KpLcncOfd3Xh04OP6AcwD8fHxDH3GGeN13Q03Z7avXP4dZcqUpUyZsm6FJmHu0X914HjKCa7qOSazrdUl9SgUHcWvG3aRcPQ4a+0Oalctn60ydH7dyox8+CaGvjEn14nSolWW157oSpVzSmXOcOvSpjHJKSdYtmYjANUrleGzsf3Z91c81/Z9/bSSsFBRo0ZNKlasxKKvF3L5FVcCkJKSwtIli2nRsrW7weVDgfyT5e1Si8vFrt2BCkDObraxxpj/AFuByjlek/F8x9lF6cLsNmvtEu+aBuOAX4FCwY7BDfv372PMq6OoW7ceV3e8ll9+Xptte8PzzldVKQBq1apNu/ZX8eqoF0lJSaFK1Wp8s3ABcz+fxeBhI4jws5aNSKDUqlqO8qWLseqXLQC88M6XzBzTl9efvJ2ZC9ZQt8Y5PN2vE9/+sJ75y5wV4Ye/OZePXunF4YQkZn+zlnKlijH4/s6kpaXz68ZdJ52jfidfvRXw0fzVPN6rI7Pe6M+wcZ9TqXwpRgy4nkkzv2PvX87koFEDb6FEbBH+M/IjqlUsTbWKpTNfv233QfYcOBLgK5L/eDweuvfsxfMjhlOiZEmaXNiUD2ZMJ+7QIe7pdp/b4eU7Ln2uvxuIydG2AadbbgZwB3C/MSYqy+DtNsB6a+1ZT9N05a+yN4O801tG+xdOuSykrfhuGcnJyWzYsJ577779pO3fLFlB6dKlfbxSTtfQES8w8a03ePedCRzYv5/a59bhhVGjaX9VR7dDkzDyeK+O3HNdc2IudBYpnLfkV24ZMJ7He3Xkzk7NOJyQxPtzf2DIG3MyXzP321+49T8TeKL3NXS7rjlHEo/xzco/ePq1WSQdy/2CnUnHUri27+u8+thtvDviPg4nJDHho6U8M3Y2AFFREXS84jyioiKZ8vy/To79lU8ZPe3rs7wCBUPXO+7i2PHjzJg2lelTJ2PqN+DNCe9QtVo1t0MTwNfsNG9Fab+1dqsxZhIwEJhkjBmJMwb6YQLUU+UJlfuGHU0OkTeST/mYECN5IPI0Fw2U01em2QNuhxDyDv0w1u0QwkKRqOAuXLRg3YGA/SXo0KDcGcdujEkHemVZcfti4DWgKbAHeMVa+9opDpFr6t8RERERv/LLZzhrrSfH89XA5XlxLg3QEBEREfFBlSQRERHxKx/cliTolCSJiIiIX+G4ao2620RERER8UCVJRERE/FJ3m4iIiIgP+WV2WzCpu01ERETEB1WSRERExC91t4mIiIj4oNltIiIiIgKokiQiIiK5EIaFJCVJIiIi4l9EGPa3qbtNRERExAdVkkRERMSv8KsjKUkSERGR3AjDLEndbSIiIiI+qJIkIiIifmkxSREREREfwnBym7rbRERERHxRJUlERET8CsNCkpIkERERyYUwzJLU3SYiIiLigypJIiIi4pdmt4mIiIj4oNltIiIiIgKokiQiIiK5EIaFJCVJIiIikgthmCWpu01ERETEB1WSRERExC/NbhMRERHxQbPbRERERAQIoUpSREQYprhBpGxaQsWhH8a6HULIK33Tm26HEBaSZvcL6vnC8a9syCRJIiIikofCMEtSkiQiIiJ+hePAbfWiiIiIiPigSpKIiIj4FY6z25QkiYiIiF9hmCOpu01ERETEF1WSRERExL8wLCUpSRIRERG/NLtNRERERABVkkRERCQXNLtNRERExIcwzJHU3SYiIiLiiypJIiIi4l8YlpKUJImIiIhfbs1uM8YUB4YBNwLlgD+AYdba2d7tTYDRwCXAX8Br1tpRgTi3uttEREQkP5sMdAZ6Ak2AT4BPjTFtjTHlgIXABuBi4GlgmDGmVyBOrEqSiIiI+OXG7DZjTEXgJqCztXaht/k5Y0w7oAfwG5AM9LPWngDWGWPqAIOAiWd7flWSRERExC9PAB+nIRG4BliSoz0dKAO0AJZ6E6QMi4Haxpgqp3eqk6mSJCIiIkFljCkFlPKxKc5aG5fxxFobD8zP8drmQFvgIaA38HuOY+zyfq0G7DybOFVJEhEREf8CW0oaAGz28RhwqhCMMQ2AT4HvgfFAUeB4jt0ynhc5k7eZlSpJIiIi4leAZ7eNxhmQnVPcP73AGNMSJ0HaCnSy1qYYY5KAwjl2zXiecLZBKkkSERGRoPJ2qcXldn9jzF3AJOBb4GZvNxzAdqByjt0znu84uyjV3SYiIiK54PEE7nE6jDF3AtOAj3AqSPFZNi8BrjTGZC36tAHWW2v3nOVbViVJRERE/HNjKUljTFWcqfyLgIFAWWNMxuZknOrSQGCSMWYkcBHwMNA/EOdXJUlERETyq5twBme3xZm1tjvLY7a1dh9wFVAHWAMMBwZZaycH4uSe9PT0QBzHdcdOEBpvRESkgCt905tuhxAWkmb3C2pxZ9P+pID9nT23fEyBuBOcuttERETEL7fu3eYmdbeJiIiI+KBKkoiIiPjlxr3b3KYkSURERPwKwxxJ3W0iIiIivihJcsHMjz+iyzVX0axpY+65sytrf/rR7ZBCjq5x3tM1znu6xn/r1Kwm+z7o4Xe/5vUrMP/Z69g9ozt/vtuNtwe05ZxSMXkSU9VysXz4+NXseb87W6bey4j7mhMdlf3PajDjyXOBvXdbgaAkKcjmzPqMZ4cNplOX63h59OsUL16cfr17sGPHdrdDCxm6xnlP1zjv6Rr/rXn9Ckx6uB0eP4NiTNVSzBt+HfFJKdw7aiGPv7uCyxpUZPaQzkRFBvbPXaGoCOYM7UK1c4rT49VvGPnh/+hz7fm82ONyV+IJBk8A/ysoCt7/pQIsPT2dcWNf4+Zbb6Nv/wdo0bIVY8a+SanSpZk+dYrb4YUEXeO8p2uc93SNHYWiInj4pibMH3E9J1LT/O7ft1Mj9hw6yh0jv+SrNdv4cMkGur20gAtql6Ndk6pnFMMfE+/iyTsuPqm9a6u6nFupBLc++wVzV23hrbm/8sjEZfS4umFmpSgv4pHgUpIURNu2bWXXrp20btM2sy06OpoWLVvz3bKlLkYWOnSN856ucd7TNXZcfVF1Hr2lKU+8u4I3P//V7/7rth1kzGc/ZUuo1u+MA6BmheKZbW2bVGXJSzdx8ONebJx0D0/feQkREadX3Wh7QVV+2nSAnX8lZrbNWbmZ6KhI2jSuelrxFBRu3bvNTUGb3WaM6Q68Z609nqWtLc49V6oDvwHDrbU/ByumYNu6ZQsA1arXyNZetWo1dmzfRmpqKpGRkS5EFjp0jfOernHe0zV2/G/Dfhr0ms7hxGSf1ZycJnzx20ltnZrVBMDuiAOgdeMqzBrciU+/28Tw93+gXpVSDL3nUsoUL8J/xjsJaGSOhCnC48lsS0tPJz0d6lYpxQZvwpPhYPxxDicep06VkrmOpyApQLlNwARzCYCJwOfAPgBjTAdgPrDA234JsMoY095auyyIcQVNYkICALFFY7O1x8bGkpaWRlJSEsWKFXMjtJCha5z3dI3znq6xY9fBRP87nULVcrE896/L+N+GfSz+eScAQ+5uxiq7l26jFgKwYM12DsYfZ+K/2/Dqpz+xbV88CZ/1zXacJ26/mCdud5K0aV//Qe8xiygeU4j4pJSTzpmQlEKJmEK5jkfyt2AmSTmT0KeBMdbahzMajDFjgOeBFkGMK2gy7pOXc/BhRntEQapB5lO6xnlP1zjv6RqfvarlYpk3/DoiIjzc89ICAGIKRXFx3XMYMn1VtmrRgjXbiIyMoFWjykz72nLFw//N3PbfJ69h3uqtTPrydwAOHDkGOF1Gvm5k5vE41abcxFPQhOO3nZuLSdYD/p2jbRwQsnNcixV3+qATExMpW65cZvvRo0eJiIggpmhRt0ILGbrGeU/XOO/pGp+dhtXLMGtwJ6KiIuj8zBw27zkCQOlihYmMjGD4vc0Zfm/zk15XsYxTuVuzcX9mW/KJVHYfTMzWBnDkaDLFY6JPOkZskWgOH03OVTwFT/hlScFMktLJnnhvBHKOXCsLxAUroGCrXsMZX7Bjx/bMf2c8r1mzlt/preKfrnHe0zXOe7rGZ+6Seufw2eBOxB9NpuOg2WzafThz25EkJ3l5/sPVfP79lpNeu/s0uvc27jpMrQolsrWVKV6YkrGF2ZBlvNGp4pH8L5iz2zzAemPMcmPM20A88LwxJgrAGHMRMBb4KogxBVWNGjWpWLESi75emNmWkpLC0iWLadb8MhcjCx26xnlP1zjv6RqfmernFOezwZ3YF5dEm8c+PSkhSUhKYe2fB6hdsSRrNu7PfCSfSGVYt0upWi7347wW/byDpnXKU6Xs3+PGujSvRXJKKst+25WreAoazW7LW/WBxkAj79e6QC2gEHACWAT8CQwKYkxB5fF46N6zF8+PGE6JkiVpcmFTPpgxnbhDh7in231uhxcSdI3znq5x3tM1zp1aFUtQvmQMq+xeAEb1uoISRQvxn/FLqVa+ONXK/91ZsW1fPHsOHWX4jB/46ImOHD6azOwVf1KuRAyD725GWno6v245eNI56vd6z+e5P/p2I4/fdhGzhnRm2HurqFSmKCPuu4xJX/3O3rikXMdTkBSg3CZgPOk+BpgFizGmqLX2qPffzYHV1toTZ3KsYyd8jqHLl6ZMnsSMaVOJizuEqd+AR/7vMS5ocqHbYYUUXeO8p2uc9wrqNS5905sBP+aTd1zMgBuaUL7r25ltE/7dhnva1SfmujeJiozg4Mc9iY7yvTTC45OWM/qztQBce0kNnrj9Ys6rUYYjR1P45qftPD11JTsOnN5sutqVSvBqnxZceV4lDicm88HiDTwz7XtOpKadVjxnKml2v6DmLbvikgP2d7ZyqUIFIudyNUkKpIKUJImIhLK8SJLkZMFOknYfDlySVKlkwUiS3JzdJiIiIgVEQbrnWqDotiQiIiIiPqiSJCIiIv6FXyFJSZKIiIj4F4Y5krrbRERERHxRJUlERET8KkiLQAaKkiQRERHxS7PbRERERARQJUlERERyI/wKSUqSRERExL8wzJHU3SYiIiLiiypJIiIi4pdmt4mIiIj4EI6z25QkiYiIiF/hWEnSmCQRERERH5QkiYiIiPig7jYRERHxS91tIiIiIgKokiQiIiK5oNltIiIiIj6ou01EREREAFWSREREJBfCsJCkJElERERyIQyzJHW3iYiIiPigSpKIiIj4pdltIiIiIj5odpuIiIiIAKokiYiISC64VUgyxkQAg4GeQGlgGdDfWrsxr8+tSpKIiIj45wng4/Q8A/QDegHNgRPAl8aYImfzdnJDSZKIiIjkS8aYwsAjwBBr7Txr7c/A7UBF4Na8Pr+SJBEREfHLE8D/TkMToBiwKKPBWnsEWAO0DOgb9EFjkkRERMSvQM5uM8aUAkr52BRnrY3L8ryK9+uOHPvtAqoFLiLfQiZJKhIVhgs4iIjkQ0mz+7kdguSBAP+dHYIzGDunod5tGYp6vx7Psd9xIM/HJIVMkiQiIiIFxmhgso/2uBzPk7xfCwPJWdoLAwmBDionJUkiIiISVN4utbhc7Lrd+7UyYLO0VwZ+C2xUJ9PAbREREcmv1gJHgNYZDcaYEkBT4Nu8PrknPT09r88hIiIickaMMSOAvkB3YDMwEqgDnG+tTT7Va8+WuttEREQkP3sGiAQmALHAUqBjXidIoEqSiIiIiE8akyQiIiLig5IkERERER+UJImIiIj4oIHbLjLGPA50stZe6XYsocQYUxwYBtwIlAP+AIZZa2e7GlgIMcZUAUYBHXBWvf0WGGitzfN1S8KRMaYezr2qBlhr33Y7nlBijDE4vyNy6qVrLaokucQY0x8Y4XYcIWoy0BnoiXNzxE+AT40xbV2MKWQYYzzAPKAqcDVwCc6quF8bY4q5GVsoMsZEA+/hzOqRwGuMsw5PpRyP99wMSvIHVZKCzBhTGRgPtCH76qESAMaYisBNQGdr7UJv83PGmHZAD+Ab14ILHRWAdcAz1tr1AMaY4cBPQCNghXuhhaShQLzbQYSwRsA6a+0etwOR/EdJUvBdhPMLrzHO2g913A0n5CQC1wDf5WhPB8oEP5zQ4/1jcnvGc2NMBeBRnLty/+JWXKHIGNMS6INTEd3mbjQhqzHwu9tBSP6kJCnIrLVzgDkATle4BJK1Nh6Yn7XNGNMcaAs85EpQIcwYMxm4F+eO3NdZa/P8hpPhwhhTCpgGPGit3a7fF3mmEbDBGPMdzofW9cBwa+1X7oYl+YHGJElIM8Y0AD4Fvsfp5pTAeglnTNL7wGfGmItcjieUvAmssNbOcDuQUGWMiQVqAaWAJ4FrgdXAfGNMexdDk3xClSQJWd6uik+BrTizCFNcDinkZMxmM8b0AC7Fqdbd62pQIcAYcw/QAqfKIXnEWpvovVlqcpZbXPzPGNMQGAgs/OdXSzhQJUlCkjHmLmAB8D+glbX2oMshhQxjTCVjzJ3eWW4AWGvTgN+AKu5FFlK64wyQ326MSTDGZHRjjjXGaJmFALLWJvi4B9jPQHU34pH8RZUkCTnGmDtxxnK8B3RXBSngquNc223AMsicpt4UZ2kAOXt3AzE52jbgzHRT91uAGGMuA74C2lprf8iy6RKcpF/CnJIkCSnGmKrARGARTrm8bJYBr8mqKAXEDzjXd4IxpjcQhzOeoyzwiotxhQxr7c6cbd7v4/3W2q3BjyhkrQY2AxONMfcDfwH9gMtxuo8lzKm7TULNTUBRnNlsu4DdWR5acTsAvF1rN+NUkT4GVuEsr9DCWrvZzdhEToe3ytwRp3ttJs5aXxcDHay1P7oYmuQTnvT0dLdjEBEREcl3VEkSERER8UFJkoiIiIgPSpJEREREfFCSJCIiIuKDkiQRERERH5QkiYgrsq7YLSKSH2kxSZECyhizGGiVozkZZ32oL4Cn8mLxTGNMTZwF+HpZa982xrTGWVyyg7U2V/e68t7rrREwIADxDAEGA9HW2hNnezwRkQyqJIkUbL/g3Ag143EN8AbOvb8+D1K15kfvuX/wt2MWTwPl8iYcEZHAUCVJpGA7Yq1dlqPtG2NMDDAM59YKK/MyAGvtYbz3cBMRCSVKkkRC02rv1xrGmJE4N6ONAq4DfrHWXmaMKYxzw9Q7ce44vxF40Vo7JeuBjDHdgf8DauLcvmFYju2tydHdZoy5GBiOcw+sFOBb4P+stX8aYzKW+a9hjLnLWuvxvqYh8AJOF2IEsBh4xFprs5yrJPAScCNQGJgOHD7jqyQicgrqbhMJTRl39d3o/Xo7UATn3nbPedtmAg8Cb+IkHUuAycaY/pkHMaYP8A6wFOd+bV8AH57yxMY0xqkslQV6AX2ABsACY0xRnK65PTh3X2/hfU0dYDlQHegN9ASqAN8ZY6p59/EA84BbgCHAPUBt4OHTuC4iIrmmSpJIAWeMyfpzXAZoCTyFk3Ss8bZ7gPustUe8r2kPdALutdZO9e4zzxgTCYwwxrwLHMMZED3bWts7yz4ncKpE/+RJ4AjQ1lqb4D3fHzgJVjNr7WJjzHGcO9pndNMNAU4AbTIGmxtjvsBJ8p7CSbSuwqlM3WSt/dS7z+fAb/ydFIqIBIySJJGC7Qqc7qys0oAFOLPP0o0xAFszEiSvdt6vs3MkWZ/iVH+a4VR7KnnbsprBqZOklsD8jAQJwFr7G06V6J+0w+leO5IlnkRgIU5yBNAaSAXmZDluqjHmI5yB4CIiAaUkSaRgW4vTNQWQjlP92Zo1QfHak+N5xsyyQ/9w3Cr8nXztz7Ftl5+YygF7/ezj6zU3c3LCR5a2ssAhH9P8/cUjInJGlCSJFGwJ1trV/nc7SRyQhFP18WUzTtcdQMUc2/xN3Y8DyudsNMZcDayz1m77h9csAl48xXH3A2WMMdHW2qzJlJYSEJE8oYHbIuFpMRADFLLWrs54AHWBEUCstXYDsAVn0HdWN/g59lKgo3cZAiBzYPZ8oI23KdVHPOcBa3PE8xDO7DtwuhAjgNtyvPZ6P/GIiJwRVZJEwtMXOInJp8aY53AGP1+IM4B6eZZqz0DgQ2PMDOA9nERmoJ9jDwdWAF8ZY17F+T0zGPgd+K93nzjgAmNMO5wK0lCc9Zy+Msa8gTMeqTvOTLZ7ALwDvucCbxljKgAW+BfQ8IyvgojIKaiSJBKGrLVpOLPbpgKPAHOB+/l7OYCM/T4GbsVJjmbiJCx3+zn2jzhrHSUD04CxOKtyd7DWJnp3ew6nG28WUN1a+ytwJU5yNAn4GKgB3GatnZ7l8LcAE3EStY9wKlLPnsk1EBHxx5Oenu5/LxEREZEwo0qSiIiIiA9KkkRERER8UJIkIiIi4oOSJBEREREflCSJiIiI+KAkSURERMQHJUkiIiIiPihJEhEREfFBSZKIiIiID/8P2cYDKqISAHkAAAAASUVORK5CYII=\n", + "image/png": 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\n", "text/plain": [ "<Figure size 720x504 with 2 Axes>" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -901,10 +914,15 @@ "# lgb.fit(X_train,y_train)\n", "pred = gb.predict(X_test)\n", "gb_accuracy = accuracy_score(y_test,pred)\n", - "print(gb_accuracy)\n", - "\n", + "#print(gb_accuracy)\n", + "print('accuracy', metrics.accuracy_score(y_test,pred) )\n", + "print('precision', metrics.precision_score(y_test,pred,average='macro'))\n", + "print('recall', metrics.recall_score(y_test,pred,average='macro'))\n", + "print('f1', metrics.f1_score(y_test,pred,average='macro'))\n", + "print(\"***Classification Report***\")\n", + "print(metrics.classification_report(y_test,pred))\n", "#confusion matrix\n", - "print(\"Confusion Matrix\")\n", + "print(\"***Confusion Matrix***\")\n", "cf = confusion_matrix(y_test, pred)\n", "df_cf = pd.DataFrame(cf, columns=np.unique(y_test), index=np.unique(pred))\n", "df_cf.index.name = 'Actual'\n", @@ -916,10 +934,42 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 58, "metadata": {}, "outputs": [], - "source": [] + "source": [ + "my2 = pd.DataFrame(data=[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]],\n", + " columns=['age', 'Medu', 'Fedu', 'traveltime', 'studytime', 'failures', 'famrel',\n", + " 'freetime', 'goout', 'health', 'absences', 'Grade', 'school_GP',\n", + " 'school_MS', 'sex_F', 'sex_M', 'address_R', 'address_U', 'famsize_GT3',\n", + " 'famsize_LE3', 'Pstatus_A', 'Pstatus_T', 'Mjob_at_home', 'Mjob_health',\n", + " 'Mjob_other', 'Mjob_services', 'Mjob_teacher', 'Fjob_at_home',\n", + " 'Fjob_health', 'Fjob_other', 'Fjob_services', 'Fjob_teacher',\n", + " 'reason_course', 'reason_home', 'reason_other', 'reason_reputation',\n", + " 'guardian_father', 'guardian_mother', 'guardian_other', 'schoolsup_no',\n", + " 'schoolsup_yes', 'famsup_no', 'famsup_yes', 'paid_no', 'paid_yes',\n", + " 'activities_no', 'activities_yes', 'nursery_no', 'nursery_yes',\n", + " 'higher_no', 'higher_yes', 'internet_no', 'internet_yes', 'romantic_no',\n", + " 'romantic_yes'])" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[1]\n" + ] + } + ], + "source": [ + "pred = gb.predict(my2)\n", + "print(pred)" + ] }, { "cell_type": "code", diff --git a/Term Project.ipynb b/Term Project.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..6af175051b972eaeb0461d969d3f293c76e56202 --- /dev/null +++ b/Term Project.ipynb @@ -0,0 +1,1090 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sn\n", + "\n", + "from sklearn.metrics import classification_report, confusion_matrix\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.model_selection import StratifiedKFold\n", + "from sklearn.model_selection import LeaveOneOut\n", + "from sklearn import tree\n", + "from sklearn.ensemble import RandomForestClassifier\n", + "from sklearn.metrics import accuracy_score\n", + "from sklearn.model_selection import cross_val_score\n", + "\n", + "from sklearn.feature_selection import RFECV\n", + "\n", + "\n", + "#데이터 로드\n", + "por = pd.read_csv(\"student-por.csv\")\n", + "math = pd.read_csv(\"student-mat.csv\")\n", + "\n", + "data = pd.concat([por, math], ignore_index=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "<class 'pandas.core.frame.DataFrame'>\n", + "RangeIndex: 1044 entries, 0 to 1043\n", + "Data columns (total 31 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 school 1044 non-null object\n", + " 1 sex 1044 non-null object\n", + " 2 age 1044 non-null int64 \n", + " 3 address 1044 non-null object\n", + " 4 famsize 1044 non-null object\n", + " 5 Pstatus 1044 non-null object\n", + " 6 Medu 1044 non-null int64 \n", + " 7 Fedu 1044 non-null int64 \n", + " 8 Mjob 1044 non-null object\n", + " 9 Fjob 1044 non-null object\n", + " 10 reason 1044 non-null object\n", + " 11 guardian 1044 non-null object\n", + " 12 traveltime 1044 non-null int64 \n", + " 13 studytime 1044 non-null int64 \n", + " 14 failures 1044 non-null int64 \n", + " 15 schoolsup 1044 non-null object\n", + " 16 famsup 1044 non-null object\n", + " 17 paid 1044 non-null object\n", + " 18 activities 1044 non-null object\n", + " 19 nursery 1044 non-null object\n", + " 20 higher 1044 non-null object\n", + " 21 internet 1044 non-null object\n", + " 22 romantic 1044 non-null object\n", + " 23 famrel 1044 non-null int64 \n", + " 24 freetime 1044 non-null int64 \n", + " 25 goout 1044 non-null int64 \n", + " 26 Dalc 1044 non-null int64 \n", + " 27 Walc 1044 non-null int64 \n", + " 28 health 1044 non-null int64 \n", + " 29 absences 1044 non-null int64 \n", + " 30 Grade 1044 non-null int64 \n", + "dtypes: int64(14), object(17)\n", + "memory usage: 253.0+ KB\n", + "None\n" + ] + }, + { + "data": { + "text/plain": [ + "(1044, 31)" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Null값이 없는 것을 확인, G1 G2 G3는 Grade로 통합\n", + "data[\"Grade\"] = data['G1']+data['G2']+data['G3']\n", + "data = data.drop(columns=['G1','G2','G3'])\n", + "print(data.info())\n", + "data.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 1296x1296 with 16 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "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>age</th>\n", + " <th>Medu</th>\n", + " <th>Fedu</th>\n", + " <th>traveltime</th>\n", + " <th>studytime</th>\n", + " <th>failures</th>\n", + " <th>famrel</th>\n", + " <th>freetime</th>\n", + " <th>goout</th>\n", + " <th>Dalc</th>\n", + " <th>Walc</th>\n", + " <th>health</th>\n", + " <th>absences</th>\n", + " <th>Grade</th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>count</th>\n", + " <td>1044.000000</td>\n", + " <td>1044.000000</td>\n", + " <td>1044.000000</td>\n", + " <td>1044.000000</td>\n", + " <td>1044.000000</td>\n", + " <td>1044.000000</td>\n", + " <td>1044.000000</td>\n", + " <td>1044.000000</td>\n", + " <td>1044.000000</td>\n", + " <td>1044.000000</td>\n", + " <td>1044.000000</td>\n", + " <td>1044.000000</td>\n", + " <td>1044.000000</td>\n", + " <td>1044.000000</td>\n", + " </tr>\n", + " <tr>\n", + " <th>mean</th>\n", + " <td>16.726054</td>\n", + " <td>2.603448</td>\n", + " <td>2.387931</td>\n", + " <td>1.522989</td>\n", + " <td>1.970307</td>\n", + " <td>0.264368</td>\n", + " <td>3.935824</td>\n", + " <td>3.201149</td>\n", + " <td>3.156130</td>\n", + " <td>1.494253</td>\n", + " <td>2.284483</td>\n", + " <td>3.543103</td>\n", + " <td>4.434866</td>\n", + " <td>33.801724</td>\n", + " </tr>\n", + " <tr>\n", + " <th>std</th>\n", + " <td>1.239975</td>\n", + " <td>1.124907</td>\n", + " <td>1.099938</td>\n", + " <td>0.731727</td>\n", + " <td>0.834353</td>\n", + " <td>0.656142</td>\n", + " <td>0.933401</td>\n", + " <td>1.031507</td>\n", + " <td>1.152575</td>\n", + " <td>0.911714</td>\n", + " <td>1.285105</td>\n", + " <td>1.424703</td>\n", + " <td>6.210017</td>\n", + " <td>9.656416</td>\n", + " </tr>\n", + " <tr>\n", + " <th>min</th>\n", + " <td>15.000000</td>\n", + " <td>0.000000</td>\n", + " <td>0.000000</td>\n", + " <td>1.000000</td>\n", + " <td>1.000000</td>\n", + " <td>0.000000</td>\n", + " <td>1.000000</td>\n", + " <td>1.000000</td>\n", + " <td>1.000000</td>\n", + " <td>1.000000</td>\n", + " <td>1.000000</td>\n", + " <td>1.000000</td>\n", + " <td>0.000000</td>\n", + " <td>4.000000</td>\n", + " </tr>\n", + " <tr>\n", + " <th>25%</th>\n", + " <td>16.000000</td>\n", + " <td>2.000000</td>\n", + " <td>1.000000</td>\n", + " <td>1.000000</td>\n", + " <td>1.000000</td>\n", + " <td>0.000000</td>\n", + " <td>4.000000</td>\n", + " <td>3.000000</td>\n", + " <td>2.000000</td>\n", + " <td>1.000000</td>\n", + " <td>1.000000</td>\n", + " <td>3.000000</td>\n", + " <td>0.000000</td>\n", + " <td>28.000000</td>\n", + " </tr>\n", + " <tr>\n", + " <th>50%</th>\n", + " <td>17.000000</td>\n", + " <td>3.000000</td>\n", + " <td>2.000000</td>\n", + " <td>1.000000</td>\n", + " <td>2.000000</td>\n", + " <td>0.000000</td>\n", + " <td>4.000000</td>\n", + " <td>3.000000</td>\n", + " <td>3.000000</td>\n", + " <td>1.000000</td>\n", + " <td>2.000000</td>\n", + " <td>4.000000</td>\n", + " <td>2.000000</td>\n", + " <td>34.000000</td>\n", + " </tr>\n", + " <tr>\n", + " <th>75%</th>\n", + " <td>18.000000</td>\n", + " <td>4.000000</td>\n", + " <td>3.000000</td>\n", + " <td>2.000000</td>\n", + " <td>2.000000</td>\n", + " <td>0.000000</td>\n", + " <td>5.000000</td>\n", + " <td>4.000000</td>\n", + " <td>4.000000</td>\n", + " <td>2.000000</td>\n", + " <td>3.000000</td>\n", + " <td>5.000000</td>\n", + " <td>6.000000</td>\n", + " <td>40.000000</td>\n", + " </tr>\n", + " <tr>\n", + " <th>max</th>\n", + " <td>22.000000</td>\n", + " <td>4.000000</td>\n", + " <td>4.000000</td>\n", + " <td>4.000000</td>\n", + " <td>4.000000</td>\n", + " <td>3.000000</td>\n", + " <td>5.000000</td>\n", + " <td>5.000000</td>\n", + " <td>5.000000</td>\n", + " <td>5.000000</td>\n", + " <td>5.000000</td>\n", + " <td>5.000000</td>\n", + " <td>75.000000</td>\n", + " <td>58.000000</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "</div>" + ], + "text/plain": [ + " age Medu Fedu traveltime studytime \\\n", + "count 1044.000000 1044.000000 1044.000000 1044.000000 1044.000000 \n", + "mean 16.726054 2.603448 2.387931 1.522989 1.970307 \n", + "std 1.239975 1.124907 1.099938 0.731727 0.834353 \n", + "min 15.000000 0.000000 0.000000 1.000000 1.000000 \n", + "25% 16.000000 2.000000 1.000000 1.000000 1.000000 \n", + "50% 17.000000 3.000000 2.000000 1.000000 2.000000 \n", + "75% 18.000000 4.000000 3.000000 2.000000 2.000000 \n", + "max 22.000000 4.000000 4.000000 4.000000 4.000000 \n", + "\n", + " failures famrel freetime goout Dalc \\\n", + "count 1044.000000 1044.000000 1044.000000 1044.000000 1044.000000 \n", + "mean 0.264368 3.935824 3.201149 3.156130 1.494253 \n", + "std 0.656142 0.933401 1.031507 1.152575 0.911714 \n", + "min 0.000000 1.000000 1.000000 1.000000 1.000000 \n", + "25% 0.000000 4.000000 3.000000 2.000000 1.000000 \n", + "50% 0.000000 4.000000 3.000000 3.000000 1.000000 \n", + "75% 0.000000 5.000000 4.000000 4.000000 2.000000 \n", + "max 3.000000 5.000000 5.000000 5.000000 5.000000 \n", + "\n", + " Walc health absences Grade \n", + "count 1044.000000 1044.000000 1044.000000 1044.000000 \n", + "mean 2.284483 3.543103 4.434866 33.801724 \n", + "std 1.285105 1.424703 6.210017 9.656416 \n", + "min 1.000000 1.000000 0.000000 4.000000 \n", + "25% 1.000000 3.000000 0.000000 28.000000 \n", + "50% 2.000000 4.000000 2.000000 34.000000 \n", + "75% 3.000000 5.000000 6.000000 40.000000 \n", + "max 5.000000 5.000000 75.000000 58.000000 " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#int형 data의 EDA를 보기 위해 numbers에 저장, Outlier가 없는 것을 확인\n", + "numbers = data.select_dtypes('int64').columns\n", + "numbers = data[numbers]\n", + "\n", + "numbers.hist(figsize=(18,18), edgecolor='white')\n", + "\n", + "plt.show()\n", + "display(numbers.describe())" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 864x864 with 2 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#각 변수간의 상관관계 분석 (숫자형만)\n", + "fig, ax = plt.subplots(figsize=(12, 12))\n", + "#corr()로 상관관계 계산, vmin-vmax로 최대 최소값 지정, cmap으로 색상 결정,\n", + "#annot로 숫자 표시 여부 결정\n", + "sn.heatmap(numbers.corr(), vmin=-1, vmax=1, \n", + " cmap='RdYlBu_r', annot=True)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "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>age</th>\n", + " <th>Medu</th>\n", + " <th>Fedu</th>\n", + " <th>traveltime</th>\n", + " <th>studytime</th>\n", + " <th>failures</th>\n", + " <th>famrel</th>\n", + " <th>freetime</th>\n", + " <th>goout</th>\n", + " <th>Dalc</th>\n", + " <th>...</th>\n", + " <th>activities_no</th>\n", + " <th>activities_yes</th>\n", + " <th>nursery_no</th>\n", + " <th>nursery_yes</th>\n", + " <th>higher_no</th>\n", + " <th>higher_yes</th>\n", + " <th>internet_no</th>\n", + " <th>internet_yes</th>\n", + " <th>romantic_no</th>\n", + " <th>romantic_yes</th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>0</th>\n", + " <td>18</td>\n", + " <td>4</td>\n", + " <td>4</td>\n", + " <td>2</td>\n", + " <td>2</td>\n", + " <td>0</td>\n", + " <td>4</td>\n", + " <td>3</td>\n", + " <td>4</td>\n", + " <td>1</td>\n", + " <td>...</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " </tr>\n", + " <tr>\n", + " <th>1</th>\n", + " <td>17</td>\n", + " <td>1</td>\n", + " <td>1</td>\n", + " <td>1</td>\n", + " <td>2</td>\n", + " <td>0</td>\n", + " <td>5</td>\n", + " <td>3</td>\n", + " <td>3</td>\n", + " <td>1</td>\n", + " <td>...</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " </tr>\n", + " <tr>\n", + " <th>2</th>\n", + " <td>15</td>\n", + " <td>1</td>\n", + " <td>1</td>\n", + " <td>1</td>\n", + " <td>2</td>\n", + " <td>0</td>\n", + " <td>4</td>\n", + " <td>3</td>\n", + " <td>2</td>\n", + " <td>2</td>\n", + " <td>...</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " </tr>\n", + " <tr>\n", + " <th>3</th>\n", + " <td>15</td>\n", + " <td>4</td>\n", + " <td>2</td>\n", + " <td>1</td>\n", + " <td>3</td>\n", + " <td>0</td>\n", + " <td>3</td>\n", + " <td>2</td>\n", + " <td>2</td>\n", + " <td>1</td>\n", + " <td>...</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " </tr>\n", + " <tr>\n", + " <th>4</th>\n", + " <td>16</td>\n", + " <td>3</td>\n", + " <td>3</td>\n", + " <td>1</td>\n", + " <td>2</td>\n", + " <td>0</td>\n", + " <td>4</td>\n", + " <td>3</td>\n", + " <td>2</td>\n", + " <td>1</td>\n", + " <td>...</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "<p>5 rows × 57 columns</p>\n", + "</div>" + ], + "text/plain": [ + " age Medu Fedu traveltime studytime failures famrel freetime goout \\\n", + "0 18 4 4 2 2 0 4 3 4 \n", + "1 17 1 1 1 2 0 5 3 3 \n", + "2 15 1 1 1 2 0 4 3 2 \n", + "3 15 4 2 1 3 0 3 2 2 \n", + "4 16 3 3 1 2 0 4 3 2 \n", + "\n", + " Dalc ... activities_no activities_yes nursery_no nursery_yes \\\n", + "0 1 ... 1 0 0 1 \n", + "1 1 ... 1 0 1 0 \n", + "2 2 ... 1 0 0 1 \n", + "3 1 ... 0 1 0 1 \n", + "4 1 ... 1 0 0 1 \n", + "\n", + " higher_no higher_yes internet_no internet_yes romantic_no romantic_yes \n", + "0 0 1 1 0 1 0 \n", + "1 0 1 0 1 1 0 \n", + "2 0 1 0 1 1 0 \n", + "3 0 1 0 1 0 1 \n", + "4 0 1 1 0 1 0 \n", + "\n", + "[5 rows x 57 columns]" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#명목형 변수를 One-Hot encoding으로 정수형으로 바꿔줌\n", + "data_dummies = pd.get_dummies(data)\n", + "\n", + "data_dummies.head(5)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "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>age</th>\n", + " <th>Medu</th>\n", + " <th>Fedu</th>\n", + " <th>traveltime</th>\n", + " <th>studytime</th>\n", + " <th>failures</th>\n", + " <th>famrel</th>\n", + " <th>freetime</th>\n", + " <th>goout</th>\n", + " <th>health</th>\n", + " <th>...</th>\n", + " <th>activities_no</th>\n", + " <th>activities_yes</th>\n", + " <th>nursery_no</th>\n", + " <th>nursery_yes</th>\n", + " <th>higher_no</th>\n", + " <th>higher_yes</th>\n", + " <th>internet_no</th>\n", + " <th>internet_yes</th>\n", + " <th>romantic_no</th>\n", + " <th>romantic_yes</th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>0</th>\n", + " <td>18</td>\n", + " <td>4</td>\n", + " <td>4</td>\n", + " <td>2</td>\n", + " <td>2</td>\n", + " <td>0</td>\n", + " <td>4</td>\n", + " <td>3</td>\n", + " <td>4</td>\n", + " <td>3</td>\n", + " <td>...</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " </tr>\n", + " <tr>\n", + " <th>1</th>\n", + " <td>17</td>\n", + " <td>1</td>\n", + " <td>1</td>\n", + " <td>1</td>\n", + " <td>2</td>\n", + " <td>0</td>\n", + " <td>5</td>\n", + " <td>3</td>\n", + " <td>3</td>\n", + " <td>3</td>\n", + " <td>...</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " </tr>\n", + " <tr>\n", + " <th>2</th>\n", + " <td>15</td>\n", + " <td>1</td>\n", + " <td>1</td>\n", + " <td>1</td>\n", + " <td>2</td>\n", + " <td>0</td>\n", + " <td>4</td>\n", + " <td>3</td>\n", + " <td>2</td>\n", + " <td>3</td>\n", + " <td>...</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " </tr>\n", + " <tr>\n", + " <th>3</th>\n", + " <td>15</td>\n", + " <td>4</td>\n", + " <td>2</td>\n", + " <td>1</td>\n", + " <td>3</td>\n", + " <td>0</td>\n", + " <td>3</td>\n", + " <td>2</td>\n", + " <td>2</td>\n", + " <td>5</td>\n", + " <td>...</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " </tr>\n", + " <tr>\n", + " <th>4</th>\n", + " <td>16</td>\n", + " <td>3</td>\n", + " <td>3</td>\n", + " <td>1</td>\n", + " <td>2</td>\n", + " <td>0</td>\n", + " <td>4</td>\n", + " <td>3</td>\n", + " <td>2</td>\n", + " <td>5</td>\n", + " <td>...</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " <td>1</td>\n", + " <td>0</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "<p>5 rows × 55 columns</p>\n", + "</div>" + ], + "text/plain": [ + " age Medu Fedu traveltime studytime failures famrel freetime goout \\\n", + "0 18 4 4 2 2 0 4 3 4 \n", + "1 17 1 1 1 2 0 5 3 3 \n", + "2 15 1 1 1 2 0 4 3 2 \n", + "3 15 4 2 1 3 0 3 2 2 \n", + "4 16 3 3 1 2 0 4 3 2 \n", + "\n", + " health ... activities_no activities_yes nursery_no nursery_yes \\\n", + "0 3 ... 1 0 0 1 \n", + "1 3 ... 1 0 1 0 \n", + "2 3 ... 1 0 0 1 \n", + "3 5 ... 0 1 0 1 \n", + "4 5 ... 1 0 0 1 \n", + "\n", + " higher_no higher_yes internet_no internet_yes romantic_no romantic_yes \n", + "0 0 1 1 0 1 0 \n", + "1 0 1 0 1 1 0 \n", + "2 0 1 0 1 1 0 \n", + "3 0 1 0 1 0 1 \n", + "4 0 1 1 0 1 0 \n", + "\n", + "[5 rows x 55 columns]" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#feature, label 분리, Walc를 자주 사용할 것이므로 y로 지정\n", + "X = data_dummies.drop(['Dalc','Walc'], axis=1)\n", + "y = data_dummies['Walc']\n", + "y_d = data_dummies['Dalc']\n", + "address_u = data_dummies['address_R']\n", + "X.head(5)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0 1\n", + "1 1\n", + "2 3\n", + "3 1\n", + "4 2\n", + "Name: Walc, dtype: int64\n", + "0 1\n", + "1 1\n", + "2 2\n", + "3 1\n", + "4 1\n", + "Name: Dalc, dtype: int64\n" + ] + } + ], + "source": [ + "print(y.head(5))\n", + "print(y_d.head(5))" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "X_train's shape : (835, 55)\n", + "X_test's shape : (209, 55)\n", + "y_train's shape : (835,)\n", + "y_test's shape : (209,)\n" + ] + } + ], + "source": [ + "#Weekend 예측\n", + "X_train, X_test, y_train, y_test = train_test_split(X,y,test_size=0.2)\n", + "print(\"X_train's shape : \", X_train.shape)\n", + "print(\"X_test's shape : \", X_test.shape)\n", + "print(\"y_train's shape : \", y_train.shape)\n", + "print(\"y_test's shape : \", y_test.shape)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: 0.712 (std: 0.453)\n", + "Optimal number of features : 34\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[ True True True True True True True True True True True True\n", + " False True True True True False True True False False False False\n", + " True True False False False True True False True True False True\n", + " True True False False False True True False False True True True\n", + " False False False False False True True]\n", + "[ 1 1 1 1 1 1 1 1 1 1 1 1 5 1 1 1 1 4 1 1 14 15 9 11\n", + " 1 1 6 20 21 1 1 17 1 1 12 1 1 1 22 13 3 1 1 16 10 1 1 1\n", + " 2 19 18 7 8 1 1]\n", + "Use RFECV\n", + "Train 정확도: 0.99\n", + "Test 정확도: 0.65\n", + "Confusion Matrix\n" + ] + }, + { + "data": { + "text/plain": [ + "<AxesSubplot:xlabel='Predicted', ylabel='Actual'>" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 720x504 with 2 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#n_jobs로 사용할 컴퓨터 core의 개수 지정\n", + "rf = RandomForestClassifier(criterion = 'entropy', n_estimators = 10,\n", + " n_jobs = 2)\n", + "\n", + "cv = LeaveOneOut()\n", + "scores = cross_val_score(rf, X, y, scoring='accuracy', cv=cv, n_jobs=-1)\n", + "print('Accuracy: %.3f (std: %.3f)'%(np.mean(scores), np.std(scores)))\n", + "rf.fit(X_train, y_train)\n", + "y_pred = rf.predict(X_test)\n", + "print('Train 정확도: %.2f' %accuracy_score(y_train, rf.predict(X_train)))\n", + "print('Test 정확도: %.2f' %accuracy_score(y_test, rf.predict(X_test)))\n", + "\n", + "min_features_to_select = 20\n", + "\n", + "#Recursive Feature Elimination(RFE)과 Cross validation을 이용하여 Feature selection 진행\n", + "rfecv = RFECV(estimator=rf, step=1, cv=StratifiedKFold(10), scoring='accuracy', \n", + " min_features_to_select=min_features_to_select)\n", + "\n", + "rfecv.fit(X,y)\n", + "\n", + "print(\"Optimal number of features : %d\" %rfecv.n_features_)\n", + "\n", + "plt.figure()\n", + "plt.xlabel(\"Number of features selected\")\n", + "plt.ylabel(\"Corss validation score (# of correct classifications)\")\n", + "plt.plot(range(min_features_to_select, len(rfecv.grid_scores_) + min_features_to_select),\n", + " rfecv.grid_scores_)\n", + "plt.show()\n", + "\n", + "print(rfecv.support_)\n", + "print(rfecv.ranking_)\n", + "\n", + "#feature selection을 반영한 X_new\n", + "X_new = rfecv.fit_transform(X, y)\n", + "\n", + "#X_new로 분할\n", + "X_train, X_test, y_train, y_test = train_test_split(X_new, y, train_size = 0.8)\n", + "k_fold = StratifiedKFold(n_splits=10, shuffle=True, random_state=0)\n", + "param_grid = {\n", + " 'n_estimators': [5, 10, 15, 20],\n", + " 'max_depth' : [2, 5, 7, 9]\n", + "}\n", + "\n", + "rf.fit(X_train, y_train)\n", + "y_pred = rf.predict(X_test)\n", + "print('Use RFECV')\n", + "print('Train 정확도: %.2f' %accuracy_score(y_train, rf.predict(X_train)))\n", + "print('Test 정확도: %.2f' %accuracy_score(y_test, rf.predict(X_test)))\n", + "\n", + "#confusion matrix\n", + "print(\"Confusion Matrix\")\n", + "cf = confusion_matrix(y_test, y_pred)\n", + "df_cf = pd.DataFrame(cf, columns=np.unique(y_test), index=np.unique(y_pred))\n", + "df_cf.index.name = 'Actual'\n", + "df_cf.columns.name = 'Predicted'\n", + "plt.figure(figsize = (10,7))\n", + "sn.set(font_scale=1.4)\n", + "sn.heatmap(df_cf, cmap='Blues', annot=True, annot_kws={\"size\": 16})" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 360x360 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "AUC : 0.6258130081300814\n" + ] + } + ], + "source": [ + "from sklearn import metrics\n", + "from sklearn.metrics import roc_auc_score\n", + "\n", + "# roc curve 곡선을 그려서 성능을 평가해 본다.\n", + "fpr, tpr, thresholds = metrics.roc_curve(y_test, y_pred,pos_label=2)\n", + "fig=plt.figure(figsize=(5,5))\n", + "plt.plot(fpr, tpr, marker='o',color='b', label=\"ROC Curve\")\n", + "\n", + "plt.xlabel(\"False Positive Rate\")\n", + "plt.ylabel(\"True Positive Rate\")\n", + "\n", + "plt.plot([0, 1], [1, 1],)\n", + "plt.plot([0, 1], [0, 1], \"r--\")\n", + "plt.title(\"ROC Curve\")\n", + "plt.legend(loc = \"lower right\")\n", + "plt.grid(True)\n", + "plt.show()\n", + "\n", + "# roc curve의 밑 면적인 auc로 성능을 평가한다.\n", + "auc = metrics.auc(fpr, tpr)\n", + "print('AUC :', auc)" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Fitting 10 folds for each of 256 candidates, totalling 2560 fits\n", + "final params {'max_depth': 12, 'min_samples_leaf': 3, 'min_samples_split': 5, 'n_estimators': 50}\n", + "best score 0.6059380378657486\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import GridSearchCV\n", + "\n", + "rf_param_grid = {\n", + " 'n_estimators' : [50,100, 150,200],\n", + " 'max_depth' : [6, 8, 10, 12],\n", + " 'min_samples_leaf' : [3, 5, 7, 10],\n", + " 'min_samples_split' : [2, 3, 5, 10]\n", + "}\n", + "\n", + "grid_s = GridSearchCV(estimator=rf,param_grid=rf_param_grid, cv=StratifiedKFold(10), n_jobs=-1, verbose=2)\n", + "grid_s.fit(X_train,y_train)\n", + "print('final params', grid_s.best_params_)\n", + "print('best score', grid_s.best_score_)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "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": "3.8.5" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/Term Project.py b/Term Project.py deleted file mode 100644 index 5289ee8030553e671179318bada03b8da8a77b4a..0000000000000000000000000000000000000000 --- a/Term Project.py +++ /dev/null @@ -1,171 +0,0 @@ -#!/usr/bin/env python -# coding: utf-8 - -# In[1]: - - -import numpy as np -import pandas as pd -import matplotlib.pyplot as plt -import seaborn as sn - -from sklearn.metrics import classification_report, confusion_matrix -from sklearn.model_selection import train_test_split -from sklearn.model_selection import StratifiedKFold -from sklearn.model_selection import LeaveOneOut -from sklearn import tree -from sklearn.ensemble import RandomForestClassifier -from sklearn.metrics import accuracy_score -from sklearn.model_selection import cross_val_score - -from sklearn.feature_selection import RFECV - - -#데이터 로드 -por = pd.read_csv("student-por.csv") -math = pd.read_csv("student-mat.csv") - -data = pd.concat([por, math], ignore_index=True) - - -# In[2]: - - -#Null값이 없는 것을 확인, G1 G2 G3는 Grade로 통합 -data["Grade"] = data['G1']+data['G2']+data['G3'] -data = data.drop(columns=['G1','G2','G3']) -print(data.info()) -data.shape - - -# In[3]: - - -#int형 data의 EDA를 보기 위해 numbers에 저장, Outlier가 없는 것을 확인 -numbers = data.select_dtypes('int64').columns -numbers = data[numbers] - -numbers.hist(figsize=(18,18), edgecolor='white') - -plt.show() -display(numbers.describe()) - - -# In[4]: - - -#각 변수간의 상관관계 분석 (숫자형만) -fig, ax = plt.subplots(figsize=(12, 12)) -#corr()로 상관관계 계산, vmin-vmax로 최대 최소값 지정, cmap으로 색상 결정, -#annot로 숫자 표시 여부 결정 -sn.heatmap(numbers.corr(), vmin=-1, vmax=1, - cmap='RdYlBu_r', annot=True) -plt.show() - - -# In[5]: - - -#명목형 변수를 One-Hot encoding으로 정수형으로 바꿔줌 -data_dummies = pd.get_dummies(data) - -data_dummies.head(5) - - -# In[6]: - - -#feature, label 분리, Walc를 자주 사용할 것이므로 y로 지정 -X = data_dummies.drop(['Dalc','Walc'], axis=1) -y = data_dummies['Walc'] -y_d = data_dummies['Dalc'] -address_u = data_dummies['address_R'] -X.head(5) - - -# In[7]: - - -print(y.head(5)) -print(y_d.head(5)) - - -# In[8]: - - -#Weekend 예측 -X_train, X_test, y_train, y_test = train_test_split(X,y,test_size=0.2) -print("X_train's shape : ", X_train.shape) -print("X_test's shape : ", X_test.shape) -print("y_train's shape : ", y_train.shape) -print("y_test's shape : ", y_test.shape) - - -# In[10]: - - -#n_jobs로 사용할 컴퓨터 core의 개수 지정 -rf = RandomForestClassifier(criterion = 'entropy', n_estimators = 10, - n_jobs = 2) - -cv = LeaveOneOut() -scores = cross_val_score(rf, X, y, scoring='accuracy', cv=cv, n_jobs=-1) -print('Accuracy: %.3f (std: %.3f)'%(np.mean(scores), np.std(scores))) -#rf.fit(X_train, y_train) -#y_pred = rf.predict(X_test) -#print('Train 정확도: %.2f' %accuracy_score(y_train, rf.predict(X_train))) -#print('Test 정확도: %.2f' %accuracy_score(y_test, rf.predict(X_test))) - -min_features_to_select = 20 - -#Recursive Feature Elimination(RFE)과 Cross validation을 이용하여 Feature selection 진행 -rfecv = RFECV(estimator=rf, step=1, cv=StratifiedKFold(10), scoring='accuracy', - min_features_to_select=min_features_to_select) - -rfecv.fit(X,y) - -print("Optimal number of features : %d" %rfecv.n_features_) - -plt.figure() -plt.xlabel("Number of features selected") -plt.ylabel("Corss validation score (# of correct classifications)") -plt.plot(range(min_features_to_select, len(rfecv.grid_scores_) + min_features_to_select), - rfecv.grid_scores_) -plt.show() - -print(rfecv.support_) -print(rfecv.ranking_) - -#feature selection을 반영한 X_new -X_new = rfecv.fit_transform(X, y) - -#X_new로 분할 -X_train, X_test, y_train, y_test = train_test_split(X_new, y, train_size = 0.8) -k_fold = StratifiedKFold(n_splits=10, shuffle=True, random_state=0) -param_grid = { - 'n_estimators': [5, 10, 15, 20], - 'max_depth' : [2, 5, 7, 9] -} - -rf.fit(X_train, y_train) -y_pred = rf.predict(X_test) -print('Use RFECV') -print('Train 정확도: %.2f' %accuracy_score(y_train, rf.predict(X_train))) -print('Test 정확도: %.2f' %accuracy_score(y_test, rf.predict(X_test))) - -#confusion matrix -print("Confusion Matrix") -cf = confusion_matrix(y_test, y_pred) -df_cf = pd.DataFrame(cf, columns=np.unique(y_test), index=np.unique(y_pred)) -df_cf.index.name = 'Actual' -df_cf.columns.name = 'Predicted' -plt.figure(figsize = (10,7)) -sn.set(font_scale=1.4) -sn.heatmap(df_cf, cmap='Blues', annot=True, annot_kws={"size": 16}) - - -# In[ ]: - - - -