673 lines
482 KiB
Plaintext
673 lines
482 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "946e852d",
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"metadata": {},
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"source": [
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"### Toymodel as an initial test\n",
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"This is only a quick test to see if the model is applicable"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "0952f099",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": 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",
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"text/plain": [
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"<Figure size 1200x1200 with 1 Axes>"
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]
|
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},
|
|
"metadata": {},
|
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"output_type": "display_data"
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},
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{
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"data": {
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"image/png": 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jZSaDiIhIKhOUS+rWrYtPP/0UjRo1giAIiIuLQ0hICI4ePYpmzZoBAIYNG4aoqCjxHGtra/HvxcXFCA4OhqurKw4ePIirV69i4MCBsLCwwCeffAIAyMjIQHBwMEaMGIE1a9Zg586dGDp0KNzc3BAYGFjhsTLIICIiksoE5ZKXX35Z6/PHH3+MZcuW4bfffhODDGtra7i6upZ7/vbt23Hq1Cns2LEDLi4uaN26NWbNmoXJkycjMjISCoUCy5cvh5eXF+bOnQsAaNq0Kfbv34/58+frFWSwXEJERFQFaDQarS0/P/+x5xQXF2PdunXIzc2Fn5+fuH/NmjWoVasWmjdvjilTpuDu3bviseTkZLRo0QIuLi7ivsDAQGg0Gpw8eVJs4+/vr3WtwMBAJCcn63VPzGQQERFJVDrnoZKdAAA8PDy0ds+YMQORkZHlnnL8+HH4+fkhLy8Ptra22LBhA3x9fQEA/fv3h6enJ9zd3XHs2DFMnjwZaWlp+PnnnwEAmZmZWgEGAPFzZmamzjYajQb37t2DlZVVhW6NQQYREZFEhgwyLl26BJVKJe5WKpWPPMXHxwepqanIzs7Gjz/+iLCwMOzZswe+vr4YPny42K5FixZwc3ND165dkZ6ejoYNG1ZurHpiuYSIiKgKKF0tUrrpCjIUCgW8vb3Rtm1bREdHo1WrVli4cGG5bdu1awcAOHfuHADA1dUV165d02pT+rl0Hsej2qhUqgpnMQAGGURERNLJDLRVUklJySPncKSmpgIA3NzcAAB+fn44fvw4rl+/LrZJTEyESqUSSy5+fn7YuXOnVj+JiYla8z4qguUSIiIiiQxZLqmoKVOmICgoCPXq1cOdO3ewdu1a7N69G9u2bUN6ejrWrl2LHj16wMnJCceOHcPYsWPRsWNHtGzZEgAQEBAAX19fvPXWW4iJiUFmZiamTp2KiIgIMXsyYsQILFmyBJMmTcLgwYORlJSE9evXIyEhQa+xMsggIiKqRq5fv46BAwfi6tWrUKvVaNmyJbZt24Zu3brh0qVL2LFjBxYsWIDc3Fx4eHggNDQUU6dOFc83MzNDfHw8Ro4cCT8/P9jY2CAsLEzruRpeXl5ISEjA2LFjsXDhQtStWxcrVqzQa/kqAMgEQRAMduc1hEajgVqthrLFMMjMFKYeDpFR3D68xNRDIDIajUYDFyc1srOztSZTGrJ/tVoNm1eXQWZR8TkK5REK7yF3w0ijjdWUmMkgIiKSyBTlkuqEQQYREZFEDDJ04+oSIiIiMgpmMoiIiKQyxBLUmpvIYJBBREQkFcslurFcQkREREbBTAYREZFE99/0XtlMhmHGUhUxyCAiIpJIBgOUS2pwlMFyCRERERkFMxlEREQSceKnbgwyiIiIpOISVp1YLiEiIiKjYCaDiIhIKgOUSwSWS4iIiOhhhpiTUfnVKVUXgwwiIiKJGGToxjkZREREZBTMZBAREUnF1SU6McggIiKSiOUS3VguISIiIqNgJoOIiEgiZjJ0Y5BBREQkEYMM3VguISIiIqNgJoOIiEgiZjJ0Y5BBREQkFZew6sRyCRERERkFMxlEREQSsVyiG4MMIiIiiRhk6MYgg4iISCIGGbpxTgYREREZBTMZREREUnF1iU4MMoiIiCRiuUQ3lkuIiIjIKJjJIIMYHPoiBod2gIebIwDgzPlMzP56K3YcPAUAqF+nFma99yqeb90ACgtz7Ew+jclzfsCNW3fEPtbOfRstGtdBLQc7ZN25iz2/pyFy8S/I/DdbbNPL/xmMGxSIhvWccfN2Dr5avweLv935ZG+WCMCnXybgs6+2au1r5OmC33+cBgC49q8G0xdtwO5DZ5BzNx/ens4YPzgQr7z0jNi+5SvTcenqLa0+pke8grHhAca/ATIIZjJ0M2mQER4ejri4OACAhYUF6tWrh4EDB+KDDz6AuTnjn+rkyvUszFzyC9Iv3YBMJsMbwe2wZs5wdHrzU1y8cgs/L4nAibOXETJyMQDggxHB+G7e2+g2aC4EQQAA7DvyF+at3IZr/2bDzdkes957FXGfDUHgkHkAAP8XfPHlrHBMnv0Dkg6dhk99Vyz4sD/y8gvx1Q97TXbv9PRq0sANG5eOFj+bm/+XHB4ZuQrZd+5h7by34aS2xY/bjmDQlG+wa9UktPTxENt98HYwBvZqL362tVE+mcGTQchggCCjBk/KMPlv8u7du2PlypXIz8/Hli1bEBERAQsLC0yZMsXg1yooKIBCoTB4vwT8uu+E1uePlm3G4NAX8WxzL7jVtkc9Nyd0evMz3MnNAwC8E7kaGUkx6PhcY+z5PQ0AsOy7XeL5lzJvY0FcIr6dPQzmZnIUFZegb9D/kLD7T6z8eT8A4O/LNzE/djveC+vGIINMwtxMDpdaqnKP/X7sPOa83w9tm9UHAEwY0h2ff5eE1NOXtIIMW2vLR/ZBVN2ZfE6GUqmEq6srPD09MXLkSPj7+2PTpk24ffs2Bg4cCAcHB1hbWyMoKAhnz57VOvenn35Cs2bNoFQqUb9+fcydO1freP369TFr1iwMHDgQKpUKw4cPf5K39tSSy2Xo3a0trK0UOHw8A0qFOQRBQH5Bkdgmr6AIJSUCnm/VsNw+7FXWeK37s/j9WAaKiksAAAqFuVYfAJCXX4A6Lg5imYboSTp/6QaaBn2A1iEzMGxqLC5l/lf6+F/LBtiQmILb2bkoKSnBT9uPID+/CC+2baTVx4K47WjgPwkdB3yKRat3oKio+EnfBlVCabmksltNZfJMxsOsrKxw8+ZNhIeH4+zZs9i0aRNUKhUmT56MHj164NSpU7CwsEBKSgr69OmDyMhI9O3bFwcPHsQ777wDJycnhIeHi/3NmTMH06dPx4wZM0x3U08J34bu2PbNeFgqzJF7Lx9vTfwKaRmZ+Pd2Du7mFSBydAhmLd0EmUyGGaNCYG5uBteH/gcXOSoEQ/t0hI2VEr8fy0C/ccvFY0m/ncbHY3ujY3xj7DtyFg08aiNiQFcAgGstdZnaNpExtW1WH0tnvAlvTxdc+zcbn321FT2GzcfBdR/CzsYSK6MHY/AH36CB/2SYm8lhZanA6tnD0MCjttjH2307oVUTD9irbPD7sfOIWroJ1/7NxsdjQ014Z6QXLmHVSSaUFsRNIDw8HFlZWdi4cSMEQcDOnTvRs2dPBAUFYePGjThw4ABeeOEFAMDNmzfh4eGBuLg4vP766xgwYABu3LiB7du3i/1NmjQJCQkJOHnyJID7mYxnnnkGGzZs0DmO/Px85Ofni581Gg08PDygbDEMMjOWVyrKwtwMdV0doLK1QkjXZ/BWiB96vr0QaRmZ6NKuCea+3xee7k4oKRHw0/YU+Hi54o+Tf2P8Z9+LfTiqbeCgtoGHqyMmDwuCJuce+o79L9CIHBWC4X07wcLcDHdy87B83W5MeTsY/uGzkXLyb1PcdrV1+/ASUw+hRsm+cxctXp6Oj8f2xlshL2DS7PX44+TfmPbOK3C0t8GWPcfw+dpd2PLVGDTzrlNuH99uSsbYT77DP3vnQqmweMJ3ULNoNBq4OKmRnZ0Nlcrw5SiNRgO1Wo16I9dDrrSuVF8l+XdxcVkfo43VlEyeyYiPj4etrS0KCwtRUlKC/v37o3fv3oiPj0e7du3Edk5OTvDx8cHp06cBAKdPn0ZISIhWX+3bt8eCBQtQXFwMMzMzAMCzzz772DFER0dj5syZBryrp1NhUTEy/vkXAPDnmUt4xrceRvTrjLHR67Dr0Bm0eXUmHNU2KCougSbnHs78+gkubE/R6uNWdi5uZeci/eJ1/HUhEycTPsJzLbxw+HgGACByyS+I+nwTXJxU+Pd2Djr9zwcAcOHyzSd7s0QPUdtZw7ueM85fuoGMf27gq/V7cXDdh2ja0A0A0KJxXSQfTceKH/Zi/pQ3yu2jbbP6KCouwcUrt9CovsuTHD5JxNUlupl8TkaXLl2QmpqKs2fP4t69e4iLizPoF9zGxuaxbaZMmYLs7Gxxu3TpksGu/zSTy2RQKLTj2FvZudDk3EOHZxujtoMttu47rvN8AFBYaPdRUiLg6o1sFBYVIzSgLX4/dh43s3IMfwNEesi5m4+My//CtZYad/MKANyfn/QgMzMZhJJHJ4+P//UP5HIZajvaGXWsZDick6GbyTMZNjY28Pb21trXtGlTFBUV4dChQ1rlkrS0NPj6+optDhw4oHXegQMH0LhxYzGLUVFKpRJKJZeNVcb0iFew4+BJXMq8DTtrS7zW/Vm82LYRQkd/DgDo//Lz+Ov/52f8r6UXose9hs+/24Vzf18HALRt5ok2vp5I/jMd2Zq7qF+3Nj4cEYzzl26IWQxHtQ1Cuj6D/SlnoVSaY8DLzyOk6zPo+fZCk903Pb2mLfgZ3Tu0gIebI67eyManXybATC5HaGBbqO2s0cCjNsZGf4dZ770KR7UNEnYfw65DaVg3fwSA+6tPUk78jRefbQQ7a0v8fjwDH87/CX2CnoO9qnLpd3pyZLL7W2X7qKlMHmSUp1GjRggJCcGwYcPwxRdfwM7ODu+//z7q1KkjlkjGjx+P5557DrNmzULfvn2RnJyMJUuW4PPPPzfx6J9OtRxssSxyIFxqqaDJycPJc5cROvpz7P79DACgkaczpke8AgeVNS5euYW5K7fh87VJ4vn38grRs0srvD88GNZWClz7Nxs7k09jzjffoKDwvxUl/YLbIeq9VyGTAYePZ+DlEQvxxynOxaAn7/L1LAyduhK3su+iloMt2rVqgMSV41HL4X4WYv2CkZi55Be8Me4L5N7Nh5dHbXwe+RYC2jcDACgVFvg5MQWffrUFBYVF8HR3wsg3uiBiwEumvC0ig6oyEz8fdvv2bbz33nvYtGkTCgoK0LFjRyxevBiNGv23/Ounn37C9OnTcfbsWbi5uWH06NGYMGGCeLx+/foYM2YMxowZo9e4Sif0cOIn1WSc+Ek12ZOa+Nlg9I+QKx9fltelJD8X5xe/xomfhhYbG/vIYw4ODli1apXO80NDQxEa+uilXhcuXJA4MiIiogowQLmkJi9hNfnETyIiIqq4ZcuWoWXLllCpVFCpVPDz88PWrf+9RycvLw8RERFwcnKCra0tQkNDce3aNa0+Ll68iODgYFhbW8PZ2RkTJ05EUZH2ww53796NNm3aQKlUwtvbW2di4FEYZBAREUlkitUldevWxaeffoqUlBQcOXIEL730EkJCQsRnRI0dOxabN2/GDz/8gD179uDKlSvo3bu3eH5xcTGCg4NRUFCAgwcPIi4uDrGxsZg+fbrYJiMjA8HBweIK0DFjxmDo0KHYtm2bfl8fU87JqKo4J4OeBpyTQTXZk5qT4T3mJ5hVck5GcX4uzi0IrdRYHR0dMXv2bLz22muoXbs21q5di9deew0AcObMGTRt2hTJycl4/vnnsXXrVvTs2RNXrlyBi8v957EsX74ckydPxo0bN6BQKDB58mQkJCTgxIn/3kvVr18/ZGVl4ddff63wuJjJICIiqgI0Go3W9uCTqB+luLgY69atQ25uLvz8/JCSkoLCwkL4+/uLbZo0aYJ69eohOTkZAJCcnIwWLVqIAQYABAYGQqPRiNmQ5ORkrT5K25T2UVEMMoiIiCSSy2UG2QDAw8MDarVa3KKjox953ePHj8PW1hZKpRIjRozAhg0b4Ovri8zMTCgUCtjb22u1d3FxQWZmJgAgMzNTK8AoPV56TFcbjUaDe/fuVfjrUyWfk0FERFQdGPJhXJcuXdIql+h6SKSPjw9SU1ORnZ2NH3/8EWFhYdizZ0/lBmIEDDKIiIiqgNLVIhWhUCjEp2W3bdsWhw8fxsKFC9G3b18UFBQgKytLK5tx7do1uLq6AgBcXV3x+++/a/VXuvrkwTYPr0i5du0aVCoVrKysKnxPLJcQERFJVFXeXVJSUoL8/Hy0bdsWFhYW2Llzp3gsLS0NFy9ehJ+fHwDAz88Px48fx/Xr18U2iYmJUKlU4qs7/Pz8tPoobVPaR0Uxk0FERCSRKd5dMmXKFAQFBaFevXq4c+cO1q5di927d2Pbtm1Qq9UYMmQIxo0bB0dHR6hUKowePRp+fn54/vnnAQABAQHw9fXFW2+9hZiYGGRmZmLq1KmIiIgQSzQjRozAkiVLMGnSJAwePBhJSUlYv349EhIS9BorgwwiIiKJTPGq9+vXr2PgwIG4evUq1Go1WrZsiW3btqFbt24AgPnz50MulyM0NBT5+fkIDAzUeq+XmZkZ4uPjMXLkSPj5+cHGxgZhYWGIiooS23h5eSEhIQFjx47FwoULUbduXaxYsQKBgYH63Rufk1EWn5NBTwM+J4Nqsif1nAzfSRsN8pyMUzG9+O4SIiIi+o8pMhnVCYMMIiIiiUwxJ6M64eoSIiIiMgpmMoiIiCSSwQDlkhr8rncGGURERBKxXKIbyyVERERkFMxkEBERScTVJboxyCAiIpKI5RLdWC4hIiIio2Amg4iISCKWS3RjkEFERCQRyyW6McggIiKSiJkM3Tgng4iIiIyCmQwiIiKpDFAuqcEP/GSQQUREJBXLJbqxXEJERERGwUwGERGRRFxdohuDDCIiIolYLtGN5RIiIiIyCmYyiIiIJGK5RDcGGURERBKxXKIbyyVERERkFMxkEBERScRMhm4MMoiIiCTinAzdGGQQERFJxEyGbpyTQUREREbBTAYREZFELJfoxiCDiIhIIpZLdGO5hIiIiIyCmQwiIiKJZDBAucQgI6maGGQQERFJJJfJIK9klFHZ86sylkuIiIjIKJjJICIikoirS3RjkEFERCQRV5foxiCDiIhIIrns/lbZPmoqzskgIiIio2Amg4iISCqZAcodNTiTwSCDiIhIIk781I3lEiIiIjIKZjKIiIgkkv3/n8r2UVMxyCAiIpKIq0t0Y7mEiIiIjIKZDCIiIon4MC7dKhRkbNq0qcIdvvLKK5IHQ0REVJ1wdYluFQoyevXqVaHOZDIZiouLKzMeIiIi0iE6Oho///wzzpw5AysrK7zwwgv47LPP4OPjI7bp3Lkz9uzZo3Xe22+/jeXLl4ufL168iJEjR2LXrl2wtbVFWFgYoqOjYW7+X2iwe/dujBs3DidPnoSHhwemTp2K8PDwCo+1QnMySkpKKrQxwCAioqdJ6aveK7vpY8+ePYiIiMBvv/2GxMREFBYWIiAgALm5uVrthg0bhqtXr4pbTEyMeKy4uBjBwcEoKCjAwYMHERcXh9jYWEyfPl1sk5GRgeDgYHTp0gWpqakYM2YMhg4dim3btlV4rJWak5GXlwdLS8vKdEFERFRtmaJc8uuvv2p9jo2NhbOzM1JSUtCxY0dxv7W1NVxdXcvtY/v27Th16hR27NgBFxcXtG7dGrNmzcLkyZMRGRkJhUKB5cuXw8vLC3PnzgUANG3aFPv378f8+fMRGBhYobHqvbqkuLgYs2bNQp06dWBra4vz588DAKZNm4avv/5a3+6IiIiqrdKJn5XdAECj0Wht+fn5FRpDdnY2AMDR0VFr/5o1a1CrVi00b94cU6ZMwd27d8VjycnJaNGiBVxcXMR9gYGB0Gg0OHnypNjG399fq8/AwEAkJydX+Oujd5Dx8ccfIzY2FjExMVAoFOL+5s2bY8WKFfp2R0RERAA8PDygVqvFLTo6+rHnlJSUYMyYMWjfvj2aN28u7u/fvz++/fZb7Nq1C1OmTMHq1avx5ptvisczMzO1AgwA4ufMzEydbTQaDe7du1ehe9K7XLJq1Sp8+eWX6Nq1K0aMGCHub9WqFc6cOaNvd0RERNWWIcslly5dgkqlEvcrlcrHnhsREYETJ05g//79WvuHDx8u/r1FixZwc3ND165dkZ6ejoYNG1ZuwHrQO5Nx+fJleHt7l9lfUlKCwsJCgwyKiIioOjDkxE+VSqW1PS7IGDVqFOLj47Fr1y7UrVtXZ9t27doBAM6dOwcAcHV1xbVr17TalH4uncfxqDYqlQpWVlYV+/pUqNUDfH19sW/fvjL7f/zxRzzzzDP6dkdERER6EAQBo0aNwoYNG5CUlAQvL6/HnpOamgoAcHNzAwD4+fnh+PHjuH79utgmMTERKpUKvr6+YpudO3dq9ZOYmAg/P78Kj1Xvcsn06dMRFhaGy5cvo6SkBD///DPS0tKwatUqxMfH69sdERFRtSX7/62yfegjIiICa9euxS+//AI7OztxDoVarYaVlRXS09Oxdu1a9OjRA05OTjh27BjGjh2Ljh07omXLlgCAgIAA+Pr64q233kJMTAwyMzMxdepUREREiBmUESNGYMmSJZg0aRIGDx6MpKQkrF+/HgkJCRUeq96ZjJCQEGzevBk7duyAjY0Npk+fjtOnT2Pz5s3o1q2bvt0RERFVW4ZcXVJRy5YtQ3Z2Njp37gw3Nzdx+/777wEACoUCO3bsQEBAAJo0aYLx48cjNDQUmzdvFvswMzNDfHw8zMzM4OfnhzfffBMDBw5EVFSU2MbLywsJCQlITExEq1atMHfuXKxYsaLCy1cBic/J6NChAxITE6WcSkRERJUgCILO4x4eHmWe9lkeT09PbNmyRWebzp074+jRo3qN70GSH8Z15MgRnD59GsD9eRpt27aVPAgiIqLqiK96103vIOOff/7BG2+8gQMHDsDe3h4AkJWVhRdeeAHr1q177AxXIiKimoJvYdVN7zkZQ4cORWFhIU6fPo1bt27h1q1bOH36NEpKSjB06FBjjJGIiIiqIb0zGXv27MHBgwe13vbm4+ODxYsXo0OHDgYdHBERUVVXgxMRlaZ3kOHh4VHuQ7eKi4vh7u5ukEERERFVByyX6KZ3uWT27NkYPXo0jhw5Iu47cuQI3nvvPcyZM8eggyMiIqrKSid+VnarqSqUyXBwcNCKtHJzc9GuXTuYm98/vaioCObm5hg8eDB69epllIESERFR9VKhIGPBggVGHgYREVH1w3KJbhUKMsLCwow9DiIiomrHFI8Vr04kP4wLAPLy8lBQUKC178HX1BIREdHTS+8gIzc3F5MnT8b69etx8+bNMseLi4sNMjAiIqKq7sFXtVemj5pK79UlkyZNQlJSEpYtWwalUokVK1Zg5syZcHd3x6pVq4wxRiIioipJJjPMVlPpncnYvHkzVq1ahc6dO2PQoEHo0KEDvL294enpiTVr1mDAgAHGGCcRERFVM3pnMm7duoUGDRoAuD//4tatWwCAF198EXv37jXs6IiIiKowU7zqvTrRO8ho0KABMjIyAABNmjTB+vXrAdzPcJS+MI2IiOhpwHKJbnoHGYMGDcKff/4JAHj//fexdOlSWFpaYuzYsZg4caLBB0hERETVk95zMsaOHSv+3d/fH2fOnEFKSgq8vb3RsmVLgw6OiIioKuPqEt0q9ZwMAPD09ISnp6chxkJERFStGKLcUYNjjIoFGYsWLapwh++++67kwRAREVUnfKy4bhUKMubPn1+hzmQyGYMMIiIiAlDBIKN0NcnT5uLuOXxMOtVY1zX5ph4CkdHceULf33JIWEFRTh81VaXnZBARET2tWC7RrSYHUERERGRCzGQQERFJJJMBcq4ueSQGGURERBLJDRBkVPb8qozlEiIiIjIKSUHGvn378Oabb8LPzw+XL18GAKxevRr79+836OCIiIiqMr4gTTe9g4yffvoJgYGBsLKywtGjR5Gff3+ZUHZ2Nj755BODD5CIiKiqKi2XVHarqfQOMj766CMsX74cX331FSwsLMT97du3xx9//GHQwREREVH1pffEz7S0NHTs2LHMfrVajaysLEOMiYiIqFrgu0t00zuT4erqinPnzpXZv3//fjRo0MAggyIiIqoOSt/CWtmtptI7yBg2bBjee+89HDp0CDKZDFeuXMGaNWswYcIEjBw50hhjJCIiqpLkBtpqKr3LJe+//z5KSkrQtWtX3L17Fx07doRSqcSECRMwevRoY4yRiIiIqiG9gwyZTIYPP/wQEydOxLlz55CTkwNfX1/Y2toaY3xERERVFudk6Cb5iZ8KhQK+vr6GHAsREVG1Ikfl51TIUXOjDL2DjC5duuh8cEhSUlKlBkREREQ1g95BRuvWrbU+FxYWIjU1FSdOnEBYWJihxkVERFTlsVyim95Bxvz588vdHxkZiZycnEoPiIiIqLrgC9J0M9jKmTfffBPffPONobojIiKias5gr3pPTk6GpaWlobojIiKq8mQyVHriJ8slD+jdu7fWZ0EQcPXqVRw5cgTTpk0z2MCIiIiqOs7J0E3vIEOtVmt9lsvl8PHxQVRUFAICAgw2MCIiIqre9AoyiouLMWjQILRo0QIODg7GGhMREVG1wImfuuk18dPMzAwBAQF82yoREREAmYH+1FR6ry5p3rw5zp8/b4yxEBERVSulmYzKbvqIjo7Gc889Bzs7Ozg7O6NXr15IS0vTapOXl4eIiAg4OTnB1tYWoaGhuHbtmlabixcvIjg4GNbW1nB2dsbEiRNRVFSk1Wb37t1o06YNlEolvL29ERsbq9/XR79bAz766CNMmDAB8fHxuHr1KjQajdZGRERExrNnzx5ERETgt99+Q2JiIgoLCxEQEIDc3FyxzdixY7F582b88MMP2LNnD65cuaK1cKO4uBjBwcEoKCjAwYMHERcXh9jYWEyfPl1sk5GRgeDgYHTp0gWpqakYM2YMhg4dim3btlV4rDJBEISKNIyKisL48eNhZ2f338kPTIkVBAEymQzFxcUVvnhVpdFooFarce1mNlQqlamHQ2QU1zX5ph4CkdHc0WjQ3MsZ2dnG+Tle+nti5uajsLSxe/wJOuTl3sGMl5+RPNYbN27A2dkZe/bsQceOHZGdnY3atWtj7dq1eO211wAAZ86cQdOmTZGcnIznn38eW7duRc+ePXHlyhW4uLgAAJYvX47Jkyfjxo0bUCgUmDx5MhISEnDixAnxWv369UNWVhZ+/fXXCo2twhM/Z86ciREjRmDXrl363DsREVGNJZPJdL7Pq6J9AChTDVAqlVAqlY89Pzs7GwDg6OgIAEhJSUFhYSH8/f3FNk2aNEG9evXEICM5ORktWrQQAwwACAwMxMiRI3Hy5Ek888wzSE5O1uqjtM2YMWMqfG8VDjJKEx6dOnWqcOdERERUMR4eHlqfZ8yYgcjISJ3nlJSUYMyYMWjfvj2aN28OAMjMzIRCoYC9vb1WWxcXF2RmZoptHgwwSo+XHtPVRqPR4N69e7CysnrsPem1hLWy0RoREVFNYsglrJcuXdIql1QkixEREYETJ05g//79lRuEkegVZDRu3PixgcatW7cqNSAiIqLqwpBP/FSpVHrNyRg1ahTi4+Oxd+9e1K1bV9zv6uqKgoICZGVlaWUzrl27BldXV7HN77//rtVf6eqTB9s8vCLl2rVrUKlUFcpiAHoGGTNnzizzxE8iIiJ6cgRBwOjRo7Fhwwbs3r0bXl5eWsfbtm0LCwsL7Ny5E6GhoQCAtLQ0XLx4EX5+fgAAPz8/fPzxx7h+/TqcnZ0BAImJiVCpVPD19RXbbNmyRavvxMREsY+K0CvI6NevnzgYIiKip51cJqv0C9L0PT8iIgJr167FL7/8Ajs7O3EOhVqthpWVFdRqNYYMGYJx48bB0dERKpUKo0ePhp+fH55//nkAQEBAAHx9ffHWW28hJiYGmZmZmDp1KiIiIsQyzYgRI7BkyRJMmjQJgwcPRlJSEtavX4+EhIQKj7XCQQbnYxAREWkzxWPFly1bBgDo3Lmz1v6VK1ciPDwcADB//nzI5XKEhoYiPz8fgYGB+Pzzz8W2ZmZmiI+Px8iRI+Hn5wcbGxuEhYUhKipKbOPl5YWEhASMHTsWCxcuRN26dbFixQoEBgZWeKwVfk6GXC5HZmbmU5HJ4HMy6GnA52RQTfaknpPx2a9/GuQ5GZO7tzLaWE2pwpmMkpISY46DiIio+jHAxM8a/OoS/V/1TkRERPfJIYO8klFCZc+vyhhkEBERSWTIJaw1kd4vSCMiIiKqCGYyiIiIJDLF6pLqhEEGERGRRKZ4TkZ1wnIJERERGQUzGURERBJx4qduDDKIiIgkksMA5ZIavISV5RIiIiIyCmYyiIiIJGK5RDcGGURERBLJUfmSQE0uKdTkeyMiIiITYiaDiIhIIplMBlkl6x2VPb8qY5BBREQkkQyVf4lqzQ0xGGQQERFJxid+6sY5GURERGQUzGQQERFVQs3NQ1QegwwiIiKJ+JwM3VguISIiIqNgJoOIiEgiLmHVjUEGERGRRHzip241+d6IiIjIhJjJICIikojlEt0YZBAREUnEJ37qxnIJERERGQUzGURERBKxXKIbgwwiIiKJuLpENwYZREREEjGToVtNDqCIiIjIhJjJICIikoirS3RjkEFERCQRX5CmG8slREREZBTMZBAREUkkhwzyShY8Knt+VcYgg4iISCKWS3RjuYSIiIiMgpkMIiIiiWT//6eyfdRUDDKIiIgkYrlEN5ZLiIiIyCiYySAiIpJIZoDVJSyXEBERURksl+jGIIOIiEgiBhm6cU4GERERGQUzGURERBJxCatuzGQQERFJJJcZZtPH3r178fLLL8Pd3R0ymQwbN27UOh4eHg6ZTKa1de/eXavNrVu3MGDAAKhUKtjb22PIkCHIycnRanPs2DF06NABlpaW8PDwQExMjP5fH73PICIiIpPJzc1Fq1atsHTp0ke26d69O65evSpu3333ndbxAQMG4OTJk0hMTER8fDz27t2L4cOHi8c1Gg0CAgLg6emJlJQUzJ49G5GRkfjyyy/1GivLJURERBKZolwSFBSEoKAgnW2USiVcXV3LPXb69Gn8+uuvOHz4MJ599lkAwOLFi9GjRw/MmTMH7u7uWLNmDQoKCvDNN99AoVCgWbNmSE1Nxbx587SCkcdhJoOIiEii0tUlld2A+9mDB7f8/HzJ49q9ezecnZ3h4+ODkSNH4ubNm+Kx5ORk2NvbiwEGAPj7+0Mul+PQoUNim44dO0KhUIhtAgMDkZaWhtu3b1d4HAwyiIiIqgAPDw+o1Wpxi46OltRP9+7dsWrVKuzcuROfffYZ9uzZg6CgIBQXFwMAMjMz4ezsrHWOubk5HB0dkZmZKbZxcXHRalP6ubRNRbBcQkREJJEMlV8dUnr2pUuXoFKpxP1KpVJSf/369RP/3qJFC7Rs2RINGzbE7t270bVr18oMVW/MZBAREUlkyNUlKpVKa5MaZDysQYMGqFWrFs6dOwcAcHV1xfXr17XaFBUV4datW+I8DldXV1y7dk2rTennR831KA+DDCIiohrsn3/+wc2bN+Hm5gYA8PPzQ1ZWFlJSUsQ2SUlJKCkpQbt27cQ2e/fuRWFhodgmMTERPj4+cHBwqPC1q3y55MKFC/Dy8sLRo0fRunXrx7YPDw9HVlZWmXXD9GR9+mUCPvtqq9a+Rp4u+P3Habh45SZahcwo97yV0YPRy7+N1r5bWTnoMOBTXLmehQtJMVDbWRtt3ET6yLmbh4Urf8WO/SdwM+sOfL3r4IOIXmjZpB4AYHHcNiTsOorMG9mwMDdDs8Z1MXZwEFo19RT7eKn/R7h8TXsi3fihPTD8jSeb1iZpTLG6JCcnR8xKAEBGRgZSU1Ph6OgIR0dHzJw5E6GhoXB1dUV6ejomTZoEb29vBAYGAgCaNm2K7t27Y9iwYVi+fDkKCwsxatQo9OvXD+7u7gCA/v37Y+bMmRgyZAgmT56MEydOYOHChZg/f75eYzV5kBEeHo64uDgA9yee1K1bF6+//jqioqLEB4BcvXoVtWrVMvFISV9NGrhh49LR4mdz8/uJszouDjiz9ROttnEbDmDxtzvg/0KzMv2M/mgtfL3dceV6llHHS6SvqXPX42xGJmKmvAFnJzU27UjBoElfYMvXk+BSW436dWtj+uje8HBzQl5BIWJ/3IPBk79E4qopcLS3Fft5N7w7+gS3Ez/bWBkmTU7GZ4p3lxw5cgRdunQRP48bNw4AEBYWhmXLluHYsWOIi4tDVlYW3N3dERAQgFmzZmmVX9asWYNRo0aha9eukMvlCA0NxaJFi8TjarUa27dvR0REBNq2bYtatWph+vTpei1fBapAkAHcnwm7cuVKFBYWIiUlBWFhYZDJZPjss89gZmamV/2Hqg5zMzlcaqnK7DcrZ3/87j/Ry78NbK21f7h+/eM+ZN+5i0lDg7Dj4CmjjpdIH3n5hdi+9zg+nzUIz7VsCAAYHRaIXcmnsHbzQYwdHISXu2pn5aaMDMGPW39H2vkr8GvTWNxvY61Ebcey/1ao6pMBlX4ouL7nd+7cGYIgPPL4tm3bHtuHo6Mj1q5dq7NNy5YtsW/fPj1Hp61KzMkofWiIh4cHevXqBX9/fyQmJgK4Xy6RyWRITU0V2588eRI9e/aESqWCnZ0dOnTogPT0dK0+58yZAzc3Nzg5OSEiIkKrrkRPxvlLN9A06AO0DpmBYVNjcSnzVrntUk9fxPG//sGbr/hp7T9z/ipmr9iKZTMHQq7vc3eJjKyouBjFJSVQKrT/r6ZUmuOPExll2hcUFuH7hGTY2VjCp6G71rGvvktCu17T0OvtuVjx/S4U/f9SQ6LqrkpkMh504sQJHDx4EJ6enuUev3z5Mjp27IjOnTsjKSkJKpUKBw4cQFFRkdhm165dcHNzw65du3Du3Dn07dsXrVu3xrBhw8rtMz8/X+uhJxqNxrA39RRq26w+ls54E96eLrj2bzY++2oregybj4PrPoSdjaVW29W/JMPHyxXtWjUQ9+UXFGLo1FjMfLcXPFwd8fflf5/0LRDpZGttiWd8PfH5tzvQoJ4LajnYIT7pKFJP/Y167v+Vd3cln8K4j1bjXn4hajva4ZuYt+Go/q9U8tarHeDbqA7UdtY4euoC5q3Yghs3NZjyTogpbov0JIcM8krWS+Q1+AVpVSLIiI+Ph62tLYqKipCfnw+5XI4lS5aU23bp0qVQq9VYt24dLCwsAACNGzfWauPg4IAlS5bAzMwMTZo0QXBwMHbu3PnIICM6OhozZ8407E095bq1/29uRfNGdfBs8/po8fJ0bNzxB94KeUE8di+vAD9uO4KJQ7Rf3hO1dBMa13dB3x7/e2JjJtJXzJT++GD29+jYNwpmcjl8G9VBcJdncPLsP2Kbdq0bYuOX43E7OxfrE37DmFmr8cOSd+HkYAcAGPR6J7Ftk4busDA3w4z5P2L80GAoFFXiRzTpYIpySXVSJb6Du3TpgmXLliE3Nxfz58+Hubk5QkNDy22bmpqKDh06iAFGeZo1awYzMzPxs5ubG44fP/7I9lOmTBEnzgD3MxkeHh4S7oQeRW1nDe96zjh/6YbW/l+SUnEvrwD9grWDib2H/8Kp9Cuo9fy7ACDWHxt2ex/jBwViytvBT2bgRDrUc6+Fb+dH4O69fOTczYezkwpjZq2Ch5uT2MbaSgnPOkp41qmF1r6eCBgYjR+3/o63+5e/eqRVU08UFZfgn2u30MDDudw2RNVFlQgybGxs4O3tDQD45ptv0KpVK3z99dcYMmRImbZWVlaP7e/hAEQmk6GkpOSR7ZVKpcEeekLly7mbj4zL/6JvLe1g4ttfDiKoYwvU+v//1ZVaFTMU9/L+m0dz9NTfGDVrDbZ8OQZedWs/kTETVZS1lRLWVkpk37mL/YfTMHF4z0e2LSkRUFBY9Mjjp89dhlwug9MDq0+oCmMqQ6cqEWQ8SC6X44MPPsC4cePQv3//MsdbtmyJuLg4FBYW6sxmkGlNW/AzundoAQ83R1y9kY1Pv0yAmVyO0MC2Ypvzl27g4NF0rF8wssz5DwcSt7JzAAA+Xq58TgZVGfsOn4EgAF4etXHx8r+I+TIeDeo5o3f3/+HuvXwsX7MTL73QDLWd7HA7OxdrfjmAa/9mo3unVgCAoycv4M8zF/F8a2/YWClx9NQFRC/bhFe6tuX3eTVhiudkVCdVLsgAgNdffx0TJ07E0qVL8dprr2kdGzVqFBYvXox+/fphypQpUKvV+O233/C///0PPj4+JhoxPezy9SwMnboSt7LvopaDLdq1aoDEleO1MhbfbkqGu7M9Xnq+iQlHSiTdndw8zFuxBZn/ZsHezhoBHVpi7OAgWJiboaSkBOcvXceGyMO4rcmFvcoGLXw8sGZBBBrVv78sX2Fhji27jmJJ3DYUFBahrqsTwkM7YtBrnR5zZaLqoUoGGebm5hg1ahRiYmIQFBSkdczJyQlJSUmYOHEiOnXqBDMzM7Ru3Rrt27c30WipPN98MvixbaZHvILpEa9UqL8X2zbG7cPlTwYmMpUenVujR+fW5R5TKiywZGa4zvObNa6L9UveM/zA6MkxwMO4anAiAzJB1xM9nlIajQZqtRrXbmZrvRGPqCa5rsl/fCOiauqORoPmXs7IzjbOz/HS3xNJqRdha1e5/nPuaPBS63pGG6spVYmHcREREVHNUyXLJURERNUCV5foxCCDiIhIIq4u0Y1BBhERkUSmeAtrdcI5GURERGQUzGQQERFJxCkZujHIICIikopRhk4slxAREZFRMJNBREQkEVeX6MYgg4iISCKuLtGN5RIiIiIyCmYyiIiIJOK8T90YZBAREUnFKEMnlkuIiIjIKJjJICIikoirS3RjkEFERCQRV5foxiCDiIhIIk7J0I1zMoiIiMgomMkgIiKSiqkMnRhkEBERScSJn7qxXEJERERGwUwGERGRRFxdohuDDCIiIok4JUM3lkuIiIjIKJjJICIikoqpDJ0YZBAREUnE1SW6sVxCRERERsFMBhERkURcXaIbgwwiIiKJOCVDNwYZREREUjHK0IlzMoiIiMgomMkgIiKSiKtLdGOQQUREJJUBJn7W4BiD5RIiIiIyDmYyiIiIJOK8T92YySAiIpJKZqBND3v37sXLL78Md3d3yGQybNy4Ueu4IAiYPn063NzcYGVlBX9/f5w9e1arza1btzBgwACoVCrY29tjyJAhyMnJ0Wpz7NgxdOjQAZaWlvDw8EBMTIx+AwWDDCIiomolNzcXrVq1wtKlS8s9HhMTg0WLFmH58uU4dOgQbGxsEBgYiLy8PLHNgAEDcPLkSSQmJiI+Ph579+7F8OHDxeMajQYBAQHw9PRESkoKZs+ejcjISHz55Zd6jZXlEiIiIolMsbokKCgIQUFB5R4TBAELFizA1KlTERISAgBYtWoVXFxcsHHjRvTr1w+nT5/Gr7/+isOHD+PZZ58FACxevBg9evTAnDlz4O7ujjVr1qCgoADffPMNFAoFmjVrhtTUVMybN08rGHkcZjKIiIgkKn2seGU34H724MEtPz9f7/FkZGQgMzMT/v7+4j61Wo127dohOTkZAJCcnAx7e3sxwAAAf39/yOVyHDp0SGzTsWNHKBQKsU1gYCDS0tJw+/btCo+HQQYREVEV4OHhAbVaLW7R0dF695GZmQkAcHFx0drv4uIiHsvMzISzs7PWcXNzczg6Omq1Ka+PB69RESyXEBERSWTI1SWXLl2CSqUS9yuVykr2bHrMZBAREUllwNUlKpVKa5MSZLi6ugIArl27prX/2rVr4jFXV1dcv35d63hRURFu3bql1aa8Ph68RkUwyCAiIpJIZqA/huLl5QVXV1fs3LlT3KfRaHDo0CH4+fkBAPz8/JCVlYWUlBSxTVJSEkpKStCuXTuxzd69e1FYWCi2SUxMhI+PDxwcHCo8HgYZRERE1UhOTg5SU1ORmpoK4P5kz9TUVFy8eBEymQxjxozBRx99hE2bNuH48eMYOHAg3N3d0atXLwBA06ZN0b17dwwbNgy///47Dhw4gFGjRqFfv35wd3cHAPTv3x8KhQJDhgzByZMn8f3332PhwoUYN26cXmPlnAwiIiKJZKj8u0v0Pf3IkSPo0qWL+Ln0F39YWBhiY2MxadIk5ObmYvjw4cjKysKLL76IX3/9FZaWluI5a9aswahRo9C1a1fI5XKEhoZi0aJF4nG1Wo3t27cjIiICbdu2Ra1atTB9+nS9lq8CgEwQBEHP+6vxNBoN1Go1rt3M1pqEQ1STXNfovzyOqLq4o9GguZczsrON83O89PfEyYzrsKtk/3c0GjQz4lhNieUSIiIiMgqWS4iIiCR68GFalemjpmKQQUREJBnfw6oLyyVERERkFMxkEBERScRyiW4MMoiIiCRisUQ3lkuIiIjIKJjJICIikojlEt0YZBAREUlkiHePGPLdJVUNgwwiIiKpOClDJ87JICIiIqNgJoOIiEgiJjJ0Y5BBREQkESd+6sZyCRERERkFMxlEREQScXWJbgwyiIiIpOKkDJ1YLiEiIiKjYCaDiIhIIiYydGOQQUREJBFXl+jGcgkREREZBTMZREREklV+dUlNLpgwyCAiIpKI5RLdWC4hIiIio2CQQUREREbBcgkREZFELJfoxiCDiIhIIj5WXDeWS4iIiMgomMkgIiKSiOUS3RhkEBERScTHiuvGcgkREREZBTMZREREUjGVoRODDCIiIom4ukQ3lkuIiIjIKJjJICIikoirS3RjkEFERCQRp2ToxiCDiIhIKkYZOnFOBhERERkFMxlEREQScXWJbgwyiIiIJOLET90YZJRDEAQAwB2NxsQjITKeO5p8Uw+ByGhy7twB8N/Pc2PRGOD3hCH6qKoYZJTjzv9/c3p7eZh4JEREVBl37tyBWq02eL8KhQKurq5oZKDfE66urlAoFAbpqyqRCcYO86qhkpISXLlyBXZ2dpDV5DxWFaHRaODh4YFLly5BpVKZejhEBsfv8SdPEATcuXMH7u7ukMuNs8YhLy8PBQUFBulLoVDA0tLSIH1VJcxklEMul6Nu3bqmHsZTR6VS8Qcw1Wj8Hn+yjJHBeJClpWWNDAwMiUtYiYiIyCgYZBAREZFRMMggk1MqlZgxYwaUSqWph0JkFPwep6cVJ34SERGRUTCTQUREREbBIIOIiIiMgkEGERERGQWDDCIiA7tw4QJkMhlSU1Mr1D48PBy9evUy6piITIFBBhlUeHg4ZDIZZDIZFAoFvL29ERUVhaKiIlMPjchgHvw+t7CwgJeXFyZNmoS8vDwAgIeHB65evYrmzZubeKREpsUnfpLBde/eHStXrkR+fj62bNmCiIgIWFhYYMqUKQa/VkFBQY183j9VfaXf54WFhUhJSUFYWBhkMhk+++wzmJmZwdXV1dRDJDI5ZjLI4JRKJVxdXeHp6YmRI0fC398fmzZtwu3btzFw4EA4ODjA2toaQUFBOHv2rNa5P/30E5o1awalUon69etj7ty5Wsfr16+PWbNmYeDAgVCpVBg+fPiTvDUiUen3uYeHB3r16gV/f38kJiYCKL9ccvLkSfTs2RMqlQp2dnbo0KED0tPTtfqcM2cO3Nzc4OTkhIiICBQWFj7JWyIyOAYZZHRWVlYoKChAeHg4jhw5gk2bNiE5ORmCIKBHjx7iD9KUlBT06dMH/fr1w/HjxxEZGYlp06YhNjZWq785c+agVatWOHr0KKZNm2aCOyLSduLECRw8ePCRWbXLly+jY8eOUCqVSEpKQkpKCgYPHqxVRty1axfS09Oxa9cuxMXFITY2tsz3PlF1w3IJGY0gCNi5cye2bduGoKAgbNy4EQcOHMALL7wAAFizZg08PDywceNGvP7665g3bx66du0qBg6NGzfGqVOnMHv2bISHh4v9vvTSSxg/frwpbolIFB8fD1tbWxQVFSE/Px9yuRxLliwpt+3SpUuhVquxbt06WFhYALj//f0gBwcHLFmyBGZmZmjSpAmCg4Oxc+dODBs2zOj3QmQszGSQwZX+8LW0tERQUBD69u2L8PBwmJubo127dmI7Jycn+Pj44PTp0wCA06dPo3379lp9tW/fHmfPnkVxcbG479lnn30yN0KkQ5cuXZCamopDhw4hLCwMgwYNQmhoaLltU1NT0aFDBzHAKE+zZs1gZmYmfnZzc8P169cNPm6iJ4lBBhlc6Q/fs2fP4t69e4iLi4NMJjNY/zY2Ngbri0gqGxsbeHt7o1WrVvjmm29w6NAhfP311+W2tbKyemx/DwcgMpkMJSUlBhkrkakwyCCDK/3hW69ePZib36/INW3aFEVFRTh06JDY7ubNm0hLS4Ovr6/Y5sCBA1p9HThwAI0bN9b6Hx5RVSOXy/HBBx9g6tSpuHfvXpnjLVu2xL59+ziRk546DDLoiWjUqBFCQkIwbNgw7N+/H3/++SfefPNN1KlTByEhIQCA8ePHY+fOnZg1axb++usvxMXFYcmSJZgwYYKJR0/0eK+//jrMzMywdOnSMsdGjRoFjUaDfv364ciRIzh79ixWr16NtLQ0E4yU6MlhkEFPzMqVK9G2bVv07NkTfn5+EAQBW7ZsEdPEbdq0wfr167Fu3To0b94c06dPR1RUlNakT6KqytzcHKNGjUJMTAxyc3O1jjk5OSEpKQk5OTno1KkT2rZti6+++krnHA2imoCveiciIiKjYCaDiIiIjIJBBhERERkFgwwiIiIyCgYZREREZBQMMoiIiMgoGGQQERGRUTDIICIiIqNgkEFURYWHh6NXr17i586dO2PMmDFPfBy7d++GTCZDVlbWI9vIZDJs3Lixwn1GRkaidevWlRrXhQsXIJPJkJqaWql+iMh4GGQQ6SE8PBwymQwymQwKhQLe3t6IiopCUVGR0a/9888/Y9asWRVqW5HAgIjI2MxNPQCi6qZ79+5YuXIl8vPzsWXLFkRERMDCwgJTpkwp07agoAAKhcIg13V0dDRIP0RETwozGUR6UiqVcHV1haenJ0aOHAl/f39s2rQJwH8ljo8//hju7u7w8fEBAFy6dAl9+vSBvb09HB0dERISggsXLoh9FhcXY9y4cbC3t4eTkxMmTZqEh5/4/3C5JD8/H5MnT4aHhweUSiW8vb3x9ddf48KFC+jSpQsAwMHBATKZTHz/S0lJCaKjo+Hl5QUrKyu0atUKP/74o9Z1tmzZgsaNG8PKygpdunTRGmdFTZ48GY0bN4a1tTUaNGiAadOmlfsG0i+++AIeHh6wtrZGnz59kJ2drXV8xYoVaNq0KSwtLdGkSRN8/vnneo+FiEyHQQZRJVlZWaGgoED8vHPnTqSlpSExMRHx8fEoLCxEYGAg7OzssG/fPhw4cAC2trbo3r27eN7cuXMRGxuLb775Bvv378etW7ewYcMGndcdOHAgvvvuOyxatAinT5/GF198AVtbW3h4eOCnn34CAKSlpeHq1atYuHAhACA6OhqrVq3C8uXLcfLkSYwdOxZvvvkm9uzZA+B+MNS7d2+8/PLLSE1NxdChQ/H+++/r/TWxs7NDbGwsTp06hYULF+Krr77C/PnztdqcO3cO69evx+bNm/Hrr7/i6NGjeOedd8Tja9aswfTp0/Hxxx/j9OnT+OSTTzBt2jTExcXpPR4iMhGBiCosLCxMCAkJEQRBEEpKSoTExERBqVQKEyZMEI+7uLgI+fn54jmrV68WfHx8hJKSEnFffn6+YGVlJWzbtk0QBEFwc3MTYmJixOOFhYVC3bp1xWsJgiB06tRJeO+99wRBEIS0tDQBgJCYmFjuOHft2iUAEG7fvi3uy8vLE6ytrYWDBw9qtR0yZIjwxhtvCIIgCFOmTBF8fX21jk+ePLlMXw8DIGzYsOGRx2fPni20bdtW/DxjxgzBzMxM+Oeff8R9W7duFeRyuXD16lVBEAShYcOGwtq1a7X6mTVrluDn5ycIgiBkZGQIAISjR48+8rpEZFqck0Gkp/j4eNja2qKwsBAlJSXo378/IiMjxeMtWrTQmofx559/4ty5c7Czs9PqJy8vD+np6cjOzsbVq1fRrl078Zi5uTmeffbZMiWTUqmpqTAzM0OnTp0qPO5z587h7t276Natm9b+goICPPPMMwCA06dPa40DAPz8/Cp8jVLff/89Fi1ahPT0dOTk5KCoqAgqlUqrTb169VCnTh2t65SUlCAtLQ12dnZIT0/HkCFDMGzYMLFNUVER1Gq13uMhItNgkEGkpy5dumDZsmVQKBRwd3eHubn2PyMbGxutzzk5OWjbti3WrFlTpq/atWtLGoOVlZXe5+Tk5AAAEhIStH65A/fnmRhKcnIyBgwYgJkzZyIwMBBqtRrr1q3D3Llz9R7rV199VSboMTMzM9hYici4GGQQ6cnGxgbe3t4Vbt+mTRt8//33cHZ2LvO/+VJubm44dOgQOnbsCOD+/9hTUlLQpk2bctu3aNECJSUl2LNnD/z9/cscL82kFBcXi/t8fX2hVCpx8eLFR2ZAmjZtKk5iLfXbb789/iYfcPDgQXh6euLDDz8U9/39999l2l28eBFXrlyBu7u7eB25XA4fHx+4uLjA3d0d58+fx4ABA/S6PhFVHZz4SWRkAwYMQK1atRASEoJ9+/YhIyMDu3fvxrvvvot//vkHAPDee+/h008/xcaNG3HmzBm88847Op9xUb9+fYSFhWHw4MHYuHGj2Of69esBAJ6enpDJZIiPj8eNGzeQk5MDOzs7TJgwAWPHjkVcXBzS09Pxxx9/YPHixeJkyhEjRuDs2bOYOHEi0tLSsHbtWsTGxup1v40aNcLFixexbt06pKenY9GiReVOYrW0tERYWBj+/PNP7Nu3D++++y769OkDV1dXAMDMmTMRHR2NRYsW4a+//sLx48excuVKzJs3T6/xEJHpMMggMjJra2vs3bsX9erVQ+/evdG0aVMMGTIEeXl5YmZj/PjxeOuttxAWFgY/Pz/Y2dnh1Vdf1dnvsmXL8Nprr+Gdd95BkyZNMGzYMOTm5gIA6tSpg5kzZ+L999+Hi4sLRo0aBQCYNWsWpk2bhujoaDRt2hTdu3dHQkICvLy8ANyfJ/HTTz9h48aNaNWqFZYvX45PPvlEr/t95ZVXMHbsWIwaNQqtW7fGwYMHMW3atDLtvL290bt3b/To0QMBAQFo2bKl1hLVoUOHYsWKFVi5ciVatGiBTp06ITY2VhwrEVV9MuFRM8uIiIiIKoGZDCIiIjIKBhlERERkFAwyiIiIyCgYZBAREZFRMMggIiIio2CQQUREREbBIIOIiIiMgkEGERERGQWDDCIiIjIKBhlERERkFAwyiIiIyCgYZBAREZFR/B8suKXHGyPGkwAAAABJRU5ErkJggg==",
|
|
"text/plain": [
|
|
"<Figure size 640x480 with 2 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Classification Report:\n",
|
|
" precision recall f1-score support\n",
|
|
"\n",
|
|
" Poor 0.87 0.87 0.87 4524\n",
|
|
" Rich 0.62 0.62 0.62 1509\n",
|
|
"\n",
|
|
" accuracy 0.81 6033\n",
|
|
" macro avg 0.74 0.75 0.74 6033\n",
|
|
"weighted avg 0.81 0.81 0.81 6033\n",
|
|
"\n",
|
|
"Index(['age', 'workclass', 'education.num', 'marital.status', 'occupation',\n",
|
|
" 'relationship', 'race', 'sex', 'capital.gain', 'capital.loss',\n",
|
|
" 'hours.per.week', 'native.country'],\n",
|
|
" dtype='object')\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"import pandas as pd\n",
|
|
"import numpy as np\n",
|
|
"import matplotlib.pyplot as plt\n",
|
|
"from sklearn.model_selection import train_test_split, RandomizedSearchCV, KFold, StratifiedKFold, GridSearchCV\n",
|
|
"from sklearn.pipeline import Pipeline\n",
|
|
"from sklearn.tree import DecisionTreeClassifier, plot_tree\n",
|
|
"from sklearn.preprocessing import LabelEncoder\n",
|
|
"from sklearn.metrics import mean_squared_error, mean_absolute_error , r2_score\n",
|
|
"from sklearn.metrics import classification_report, confusion_matrix, ConfusionMatrixDisplay\n",
|
|
"from scipy.stats import randint\n",
|
|
"\n",
|
|
"# Load dataset\n",
|
|
"df = pd.read_csv('./Datasets/adult.csv', comment = '#')\n",
|
|
"\n",
|
|
"# First, create a copy of the dataframe to avoid modifying the original\n",
|
|
"df_encoded = df.copy()\n",
|
|
"df_encoded.drop(['fnlwgt', 'education'], axis=1, inplace=True)\n",
|
|
"\n",
|
|
"# drop all rows that contain '?'\n",
|
|
"df_encoded = df_encoded[(df_encoded != '?').all(axis=1)]\n",
|
|
"\n",
|
|
"# Apply label encoding to categorical columns\n",
|
|
"categorical_columns = ['workclass', 'marital.status', 'occupation', \n",
|
|
" 'relationship', 'race', 'sex', 'native.country', 'income']\n",
|
|
"\n",
|
|
"for column in categorical_columns:\n",
|
|
" le = LabelEncoder()\n",
|
|
" df_encoded[column] = le.fit_transform(df_encoded[column])\n",
|
|
"\n",
|
|
"# Now properly separate features and target\n",
|
|
"X = df_encoded.drop(columns=['income'])\n",
|
|
"y = df_encoded['income']\n",
|
|
"\n",
|
|
"# Split the data\n",
|
|
"X_train_val, X_test, y_train_val, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
|
|
"X_train, X_val, y_train, y_val = train_test_split(X_train_val, y_train_val, test_size=0.25, random_state=42)\n",
|
|
"\n",
|
|
"\n",
|
|
"# Build pipeline\n",
|
|
"model = Pipeline([\n",
|
|
" ('full_dt_classifier', DecisionTreeClassifier(random_state=42)) # Train Decision Tree Regressor\n",
|
|
"])\n",
|
|
"\n",
|
|
"# Train the model\n",
|
|
"model.fit(X_train, y_train)\n",
|
|
"y_pred = model.predict(X_val)\n",
|
|
"\n",
|
|
"# Visualize the decision tree\n",
|
|
"plt.figure(figsize=(12, 12))\n",
|
|
"plot_tree(\n",
|
|
" model.named_steps['full_dt_classifier'],\n",
|
|
" feature_names=X.columns,\n",
|
|
" class_names=[\"Poor\", \"Rich\"],\n",
|
|
" filled=True,\n",
|
|
" rounded=True,\n",
|
|
" max_depth=5, # Keep tree shallow for readability\n",
|
|
" fontsize=3,\n",
|
|
" precision=2 # Limit decimals\n",
|
|
")\n",
|
|
"\n",
|
|
"plt.savefig('decision_tree.pdf', format='pdf', dpi=300)\n",
|
|
"plt.show()\n",
|
|
"\n",
|
|
"CM = confusion_matrix(y_val, y_pred)\n",
|
|
"disp = ConfusionMatrixDisplay(confusion_matrix=CM, display_labels=[\"Poor\", \"Rich\"])\n",
|
|
"disp.plot(cmap=\"Blues\")\n",
|
|
"plt.title(\"Confusion Matrix\")\n",
|
|
"plt.show() \n",
|
|
"\n",
|
|
"print(\"Classification Report:\")\n",
|
|
"print(classification_report(y_val, y_pred, target_names=[\"Poor\", \"Rich\"]))\n",
|
|
"\n",
|
|
"print(X_train_val.columns)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "bfaae28c",
|
|
"metadata": {},
|
|
"source": [
|
|
"### Hyperparameter tuning\n",
|
|
"I think this section is pretty unecessary. It can probably be removed, but I'm going to keep it for now, just in case. "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 4,
|
|
"id": "e567e4e9",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"ename": "KeyboardInterrupt",
|
|
"evalue": "",
|
|
"output_type": "error",
|
|
"traceback": [
|
|
"\u001b[31m---------------------------------------------------------------------------\u001b[39m",
|
|
"\u001b[31mKeyboardInterrupt\u001b[39m Traceback (most recent call last)",
|
|
"\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[4]\u001b[39m\u001b[32m, line 8\u001b[39m\n\u001b[32m 6\u001b[39m skf = StratifiedKFold(n_splits=\u001b[32m10\u001b[39m, shuffle=\u001b[38;5;28;01mTrue\u001b[39;00m, random_state=\u001b[32m42\u001b[39m)\n\u001b[32m 7\u001b[39m grid_search = GridSearchCV(model, param_grid, scoring=\u001b[33m'\u001b[39m\u001b[33maccuracy\u001b[39m\u001b[33m'\u001b[39m, cv=skf, n_jobs=-\u001b[32m1\u001b[39m)\n\u001b[32m----> \u001b[39m\u001b[32m8\u001b[39m \u001b[43mgrid_search\u001b[49m\u001b[43m.\u001b[49m\u001b[43mfit\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX_train\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my_train\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 11\u001b[39m \u001b[38;5;66;03m# Best model training\u001b[39;00m\n\u001b[32m 12\u001b[39m best_model = grid_search.best_estimator_\n",
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"\u001b[36mFile \u001b[39m\u001b[32m~/Documents/MLP/Projects/MLPproject/.venv/lib/python3.12/site-packages/sklearn/base.py:1365\u001b[39m, in \u001b[36m_fit_context.<locals>.decorator.<locals>.wrapper\u001b[39m\u001b[34m(estimator, *args, **kwargs)\u001b[39m\n\u001b[32m 1358\u001b[39m estimator._validate_params()\n\u001b[32m 1360\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m config_context(\n\u001b[32m 1361\u001b[39m skip_parameter_validation=(\n\u001b[32m 1362\u001b[39m prefer_skip_nested_validation \u001b[38;5;129;01mor\u001b[39;00m global_skip_validation\n\u001b[32m 1363\u001b[39m )\n\u001b[32m 1364\u001b[39m ):\n\u001b[32m-> \u001b[39m\u001b[32m1365\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfit_method\u001b[49m\u001b[43m(\u001b[49m\u001b[43mestimator\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
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"\u001b[36mFile \u001b[39m\u001b[32m~/Documents/MLP/Projects/MLPproject/.venv/lib/python3.12/site-packages/sklearn/model_selection/_search.py:1051\u001b[39m, in \u001b[36mBaseSearchCV.fit\u001b[39m\u001b[34m(self, X, y, **params)\u001b[39m\n\u001b[32m 1045\u001b[39m results = \u001b[38;5;28mself\u001b[39m._format_results(\n\u001b[32m 1046\u001b[39m all_candidate_params, n_splits, all_out, all_more_results\n\u001b[32m 1047\u001b[39m )\n\u001b[32m 1049\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m results\n\u001b[32m-> \u001b[39m\u001b[32m1051\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_run_search\u001b[49m\u001b[43m(\u001b[49m\u001b[43mevaluate_candidates\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 1053\u001b[39m \u001b[38;5;66;03m# multimetric is determined here because in the case of a callable\u001b[39;00m\n\u001b[32m 1054\u001b[39m \u001b[38;5;66;03m# self.scoring the return type is only known after calling\u001b[39;00m\n\u001b[32m 1055\u001b[39m first_test_score = all_out[\u001b[32m0\u001b[39m][\u001b[33m\"\u001b[39m\u001b[33mtest_scores\u001b[39m\u001b[33m\"\u001b[39m]\n",
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"\u001b[36mFile \u001b[39m\u001b[32m~/Documents/MLP/Projects/MLPproject/.venv/lib/python3.12/site-packages/sklearn/model_selection/_search.py:1605\u001b[39m, in \u001b[36mGridSearchCV._run_search\u001b[39m\u001b[34m(self, evaluate_candidates)\u001b[39m\n\u001b[32m 1603\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34m_run_search\u001b[39m(\u001b[38;5;28mself\u001b[39m, evaluate_candidates):\n\u001b[32m 1604\u001b[39m \u001b[38;5;250m \u001b[39m\u001b[33;03m\"\"\"Search all candidates in param_grid\"\"\"\u001b[39;00m\n\u001b[32m-> \u001b[39m\u001b[32m1605\u001b[39m \u001b[43mevaluate_candidates\u001b[49m\u001b[43m(\u001b[49m\u001b[43mParameterGrid\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mparam_grid\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n",
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"\u001b[36mFile \u001b[39m\u001b[32m~/Documents/MLP/Projects/MLPproject/.venv/lib/python3.12/site-packages/sklearn/model_selection/_search.py:997\u001b[39m, in \u001b[36mBaseSearchCV.fit.<locals>.evaluate_candidates\u001b[39m\u001b[34m(candidate_params, cv, more_results)\u001b[39m\n\u001b[32m 989\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m.verbose > \u001b[32m0\u001b[39m:\n\u001b[32m 990\u001b[39m \u001b[38;5;28mprint\u001b[39m(\n\u001b[32m 991\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mFitting \u001b[39m\u001b[38;5;132;01m{0}\u001b[39;00m\u001b[33m folds for each of \u001b[39m\u001b[38;5;132;01m{1}\u001b[39;00m\u001b[33m candidates,\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 992\u001b[39m \u001b[33m\"\u001b[39m\u001b[33m totalling \u001b[39m\u001b[38;5;132;01m{2}\u001b[39;00m\u001b[33m fits\u001b[39m\u001b[33m\"\u001b[39m.format(\n\u001b[32m 993\u001b[39m n_splits, n_candidates, n_candidates * n_splits\n\u001b[32m 994\u001b[39m )\n\u001b[32m 995\u001b[39m )\n\u001b[32m--> \u001b[39m\u001b[32m997\u001b[39m out = \u001b[43mparallel\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 998\u001b[39m \u001b[43m \u001b[49m\u001b[43mdelayed\u001b[49m\u001b[43m(\u001b[49m\u001b[43m_fit_and_score\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 999\u001b[39m \u001b[43m \u001b[49m\u001b[43mclone\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbase_estimator\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 1000\u001b[39m \u001b[43m \u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 1001\u001b[39m \u001b[43m \u001b[49m\u001b[43my\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 1002\u001b[39m \u001b[43m \u001b[49m\u001b[43mtrain\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtrain\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 1003\u001b[39m \u001b[43m \u001b[49m\u001b[43mtest\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtest\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 1004\u001b[39m \u001b[43m \u001b[49m\u001b[43mparameters\u001b[49m\u001b[43m=\u001b[49m\u001b[43mparameters\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 1005\u001b[39m \u001b[43m \u001b[49m\u001b[43msplit_progress\u001b[49m\u001b[43m=\u001b[49m\u001b[43m(\u001b[49m\u001b[43msplit_idx\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mn_splits\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 1006\u001b[39m \u001b[43m \u001b[49m\u001b[43mcandidate_progress\u001b[49m\u001b[43m=\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcand_idx\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mn_candidates\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 1007\u001b[39m \u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mfit_and_score_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 1008\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 1009\u001b[39m \u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[43mcand_idx\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mparameters\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[43msplit_idx\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrain\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtest\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mproduct\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 1010\u001b[39m \u001b[43m \u001b[49m\u001b[38;5;28;43menumerate\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mcandidate_params\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 1011\u001b[39m \u001b[43m \u001b[49m\u001b[38;5;28;43menumerate\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mcv\u001b[49m\u001b[43m.\u001b[49m\u001b[43msplit\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mrouted_params\u001b[49m\u001b[43m.\u001b[49m\u001b[43msplitter\u001b[49m\u001b[43m.\u001b[49m\u001b[43msplit\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 1012\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 1013\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 1015\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(out) < \u001b[32m1\u001b[39m:\n\u001b[32m 1016\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[32m 1017\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mNo fits were performed. \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 1018\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mWas the CV iterator empty? \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 1019\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mWere there no candidates?\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 1020\u001b[39m )\n",
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"\u001b[36mFile \u001b[39m\u001b[32m~/Documents/MLP/Projects/MLPproject/.venv/lib/python3.12/site-packages/sklearn/utils/parallel.py:82\u001b[39m, in \u001b[36mParallel.__call__\u001b[39m\u001b[34m(self, iterable)\u001b[39m\n\u001b[32m 73\u001b[39m warning_filters = warnings.filters\n\u001b[32m 74\u001b[39m iterable_with_config_and_warning_filters = (\n\u001b[32m 75\u001b[39m (\n\u001b[32m 76\u001b[39m _with_config_and_warning_filters(delayed_func, config, warning_filters),\n\u001b[32m (...)\u001b[39m\u001b[32m 80\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m delayed_func, args, kwargs \u001b[38;5;129;01min\u001b[39;00m iterable\n\u001b[32m 81\u001b[39m )\n\u001b[32m---> \u001b[39m\u001b[32m82\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m.\u001b[49m\u001b[34;43m__call__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43miterable_with_config_and_warning_filters\u001b[49m\u001b[43m)\u001b[49m\n",
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"\u001b[36mFile \u001b[39m\u001b[32m~/Documents/MLP/Projects/MLPproject/.venv/lib/python3.12/site-packages/joblib/parallel.py:2072\u001b[39m, in \u001b[36mParallel.__call__\u001b[39m\u001b[34m(self, iterable)\u001b[39m\n\u001b[32m 2066\u001b[39m \u001b[38;5;66;03m# The first item from the output is blank, but it makes the interpreter\u001b[39;00m\n\u001b[32m 2067\u001b[39m \u001b[38;5;66;03m# progress until it enters the Try/Except block of the generator and\u001b[39;00m\n\u001b[32m 2068\u001b[39m \u001b[38;5;66;03m# reaches the first `yield` statement. This starts the asynchronous\u001b[39;00m\n\u001b[32m 2069\u001b[39m \u001b[38;5;66;03m# dispatch of the tasks to the workers.\u001b[39;00m\n\u001b[32m 2070\u001b[39m \u001b[38;5;28mnext\u001b[39m(output)\n\u001b[32m-> \u001b[39m\u001b[32m2072\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m output \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m.return_generator \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;43mlist\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43moutput\u001b[49m\u001b[43m)\u001b[49m\n",
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"\u001b[36mFile \u001b[39m\u001b[32m~/Documents/MLP/Projects/MLPproject/.venv/lib/python3.12/site-packages/joblib/parallel.py:1682\u001b[39m, in \u001b[36mParallel._get_outputs\u001b[39m\u001b[34m(self, iterator, pre_dispatch)\u001b[39m\n\u001b[32m 1679\u001b[39m \u001b[38;5;28;01myield\u001b[39;00m\n\u001b[32m 1681\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m._backend.retrieval_context():\n\u001b[32m-> \u001b[39m\u001b[32m1682\u001b[39m \u001b[38;5;28;01myield from\u001b[39;00m \u001b[38;5;28mself\u001b[39m._retrieve()\n\u001b[32m 1684\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mGeneratorExit\u001b[39;00m:\n\u001b[32m 1685\u001b[39m \u001b[38;5;66;03m# The generator has been garbage collected before being fully\u001b[39;00m\n\u001b[32m 1686\u001b[39m \u001b[38;5;66;03m# consumed. This aborts the remaining tasks if possible and warn\u001b[39;00m\n\u001b[32m 1687\u001b[39m \u001b[38;5;66;03m# the user if necessary.\u001b[39;00m\n\u001b[32m 1688\u001b[39m \u001b[38;5;28mself\u001b[39m._exception = \u001b[38;5;28;01mTrue\u001b[39;00m\n",
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"\u001b[36mFile \u001b[39m\u001b[32m~/Documents/MLP/Projects/MLPproject/.venv/lib/python3.12/site-packages/joblib/parallel.py:1800\u001b[39m, in \u001b[36mParallel._retrieve\u001b[39m\u001b[34m(self)\u001b[39m\n\u001b[32m 1789\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m.return_ordered:\n\u001b[32m 1790\u001b[39m \u001b[38;5;66;03m# Case ordered: wait for completion (or error) of the next job\u001b[39;00m\n\u001b[32m 1791\u001b[39m \u001b[38;5;66;03m# that have been dispatched and not retrieved yet. If no job\u001b[39;00m\n\u001b[32m (...)\u001b[39m\u001b[32m 1795\u001b[39m \u001b[38;5;66;03m# control only have to be done on the amount of time the next\u001b[39;00m\n\u001b[32m 1796\u001b[39m \u001b[38;5;66;03m# dispatched job is pending.\u001b[39;00m\n\u001b[32m 1797\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m (nb_jobs == \u001b[32m0\u001b[39m) \u001b[38;5;129;01mor\u001b[39;00m (\n\u001b[32m 1798\u001b[39m \u001b[38;5;28mself\u001b[39m._jobs[\u001b[32m0\u001b[39m].get_status(timeout=\u001b[38;5;28mself\u001b[39m.timeout) == TASK_PENDING\n\u001b[32m 1799\u001b[39m ):\n\u001b[32m-> \u001b[39m\u001b[32m1800\u001b[39m \u001b[43mtime\u001b[49m\u001b[43m.\u001b[49m\u001b[43msleep\u001b[49m\u001b[43m(\u001b[49m\u001b[32;43m0.01\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[32m 1801\u001b[39m \u001b[38;5;28;01mcontinue\u001b[39;00m\n\u001b[32m 1803\u001b[39m \u001b[38;5;28;01melif\u001b[39;00m nb_jobs == \u001b[32m0\u001b[39m:\n\u001b[32m 1804\u001b[39m \u001b[38;5;66;03m# Case unordered: jobs are added to the list of jobs to\u001b[39;00m\n\u001b[32m 1805\u001b[39m \u001b[38;5;66;03m# retrieve `self._jobs` only once completed or in error, which\u001b[39;00m\n\u001b[32m (...)\u001b[39m\u001b[32m 1811\u001b[39m \u001b[38;5;66;03m# timeouts before any other dispatched job has completed and\u001b[39;00m\n\u001b[32m 1812\u001b[39m \u001b[38;5;66;03m# been added to `self._jobs` to be retrieved.\u001b[39;00m\n",
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"\u001b[31mKeyboardInterrupt\u001b[39m: "
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]
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}
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],
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"source": [
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"param_grid = {\n",
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" 'full_dt_classifier__max_depth': [None, 10, 11, 12, 13, 14, 15, 16],\n",
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" 'full_dt_classifier__min_samples_split': [3, 4, 5, 6, 7, 8, 9],\n",
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" 'full_dt_classifier__min_samples_leaf': [1, 2, 3, 4, 5]\n",
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" }\n",
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"skf = StratifiedKFold(n_splits=10, shuffle=True, random_state=42)\n",
|
|
"grid_search = GridSearchCV(model, param_grid, scoring='accuracy', cv=skf, n_jobs=-1)\n",
|
|
"grid_search.fit(X_train, y_train)\n",
|
|
"\n",
|
|
"\n",
|
|
"# Best model training\n",
|
|
"best_model = grid_search.best_estimator_\n",
|
|
"y_pred_best = best_model.predict(X_val)\n",
|
|
"\n",
|
|
"print(\"Classification Report:\")\n",
|
|
"print(classification_report(y_val, y_pred_best, target_names=[\"Poor\", \"Rich\"]))\n",
|
|
"\n",
|
|
"best_max_depth = best_model.named_steps['full_dt_classifier'].max_depth\n",
|
|
"best_min_samples_split = best_model.named_steps['full_dt_classifier'].min_samples_split\n",
|
|
"best_min_samples_leaf = best_model.named_steps['full_dt_classifier'].min_samples_leaf\n",
|
|
"\n",
|
|
"print(f'Best max_depth: {best_max_depth}')\n",
|
|
"print(f'Best min_samples_split: {best_min_samples_split}')\n",
|
|
"print(f'Best min_samples_leaf: {best_min_samples_leaf}')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "a37f45b4",
|
|
"metadata": {},
|
|
"source": [
|
|
"### Classifier comparison\n",
|
|
"This is taken from the ensemble lab. A lot of models are excluded, but they are easy to implement into the class, for now It's kept short to minimize the execution time. We can also tune more parameters for each model, but of course that would also increase the execution time."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 3,
|
|
"id": "e68b1ea9",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"from sklearn.model_selection import GridSearchCV, StratifiedKFold\n",
|
|
"import time\n",
|
|
"\n",
|
|
"from sklearn.preprocessing import StandardScaler\n",
|
|
"from sklearn.metrics import (accuracy_score, precision_score, \n",
|
|
" recall_score, f1_score, \n",
|
|
" confusion_matrix, ConfusionMatrixDisplay)\n",
|
|
"from sklearn.ensemble import (RandomForestClassifier, BaggingClassifier, \n",
|
|
" AdaBoostClassifier, GradientBoostingClassifier)\n",
|
|
"from xgboost import XGBClassifier # Requires installation of the package ; Not a native function in sklearn\n",
|
|
"from lightgbm import LGBMClassifier # Requires installation of the package; Not a native function in sklearn\n",
|
|
"from catboost import CatBoostClassifier # Requires installation of the package; Not a native function in sklearn\n",
|
|
"\n",
|
|
"class ClassifierComparisonOpt:\n",
|
|
" def __init__(self, X, y, test_size=0.25, use_bootstrap=True, random_state=42, cv_folds=10):\n",
|
|
" # Split data stratified by labels\n",
|
|
" X_train, X_test, y_train, y_test = train_test_split(\n",
|
|
" X, y, test_size=test_size, stratify=y, random_state=random_state)\n",
|
|
"\n",
|
|
" # Scale features\n",
|
|
" #scaler = StandardScaler()\n",
|
|
" #self.X_train = scaler.fit_transform(X_train)\n",
|
|
" #self.X_test = scaler.transform(X_test)\n",
|
|
"\n",
|
|
" # Scaling not necessary for decision trees\n",
|
|
" self.X_train = X_train\n",
|
|
" self.X_test = X_test\n",
|
|
"\n",
|
|
" self.y_train = y_train\n",
|
|
" self.y_test = y_test\n",
|
|
" self.use_bootstrap = use_bootstrap\n",
|
|
" self.cv_folds = cv_folds\n",
|
|
" self.models = {}\n",
|
|
" self.results = {}\n",
|
|
" self.results_df = None\n",
|
|
" self.feature_names = list(X.columns)\n",
|
|
"\n",
|
|
" def get_models_with_params(self):\n",
|
|
" return {\n",
|
|
" 'Decision Tree': (DecisionTreeClassifier(random_state=42), {\n",
|
|
" 'max_depth': [None, 5, 10, 20],\n",
|
|
" 'min_samples_split': [2, 5, 10],\n",
|
|
" #'min_samples_leaf': [2, 4, 6]\n",
|
|
" }),\n",
|
|
" 'Random Forest': (RandomForestClassifier(bootstrap=self.use_bootstrap, random_state=42), {\n",
|
|
" 'n_estimators': [50, 100, 200],\n",
|
|
" 'max_depth': [None, 5, 10, 20],\n",
|
|
" 'min_samples_split': [2, 5, 10],\n",
|
|
" #'min_samples_leaf': [2, 4, 6]\n",
|
|
" }),\n",
|
|
" 'XGBoost': (XGBClassifier(eval_metric='mlogloss', random_state=42), {\n",
|
|
" 'n_estimators': [50, 100, 200],\n",
|
|
" 'learning_rate': [0.01, 0.1, 0.2, 0.5, 1.0],\n",
|
|
" 'max_depth': [3, 5, 10]\n",
|
|
" })\n",
|
|
" }\n",
|
|
"\n",
|
|
" def fit_models(self, models_with_params=None):\n",
|
|
" # Set self.get_models_with_params() as a default parameter distribution\n",
|
|
" if models_with_params == None:\n",
|
|
" models_with_params = self.get_models_with_params()\n",
|
|
"\n",
|
|
" results_list = []\n",
|
|
" cv = StratifiedKFold(n_splits=self.cv_folds, shuffle=True, random_state=42)\n",
|
|
"\n",
|
|
" for name, (model, param_grid) in models_with_params.items():\n",
|
|
" print(f\"Tuning {name} ...\")\n",
|
|
" \n",
|
|
" grid_search = GridSearchCV(model, param_grid, scoring='accuracy', cv=cv, n_jobs=-1)\n",
|
|
" \n",
|
|
" start_train = time.time()\n",
|
|
" grid_search.fit(self.X_train, self.y_train)\n",
|
|
" end_train = time.time()\n",
|
|
"\n",
|
|
" best_model = grid_search.best_estimator_\n",
|
|
" y_pred = best_model.predict(self.X_test)\n",
|
|
" end_pred = time.time()\n",
|
|
"\n",
|
|
" self.models[name] = {\n",
|
|
" 'model': best_model,\n",
|
|
" 'confusion_matrix': confusion_matrix(self.y_test, y_pred)\n",
|
|
" }\n",
|
|
"\n",
|
|
" metrics = {\n",
|
|
" 'Model': name,\n",
|
|
" 'Accuracy': accuracy_score(self.y_test, y_pred),\n",
|
|
" 'Precision': precision_score(self.y_test, y_pred, average='weighted', zero_division=0),\n",
|
|
" 'Recall': recall_score(self.y_test, y_pred, average='weighted'),\n",
|
|
" 'F1 Score': f1_score(self.y_test, y_pred, average='weighted'),\n",
|
|
" 'Best Params': grid_search.best_params_,\n",
|
|
" 'Training Time (s)': (end_train - start_train),\n",
|
|
" 'Prediction Time (s)': (end_pred - end_train),\n",
|
|
" 'Total Time (s)': (end_pred - start_train)\n",
|
|
" }\n",
|
|
"\n",
|
|
" results_list.append(metrics)\n",
|
|
"\n",
|
|
" self.results_df = pd.DataFrame(results_list)\n",
|
|
"\n",
|
|
" def print_summary(self):\n",
|
|
" print(\"\\n------ Results Sorted by Accuracy ------\")\n",
|
|
" print(self.results_df.sort_values(by='Accuracy', ascending=False).to_string(index=False))\n",
|
|
"\n",
|
|
" print(\"\\n------ Results Sorted by Total Time ------\")\n",
|
|
" print(self.results_df.sort_values(by='Total Time (s)', ascending=True).to_string(index=False))\n",
|
|
"\n",
|
|
" # Show feature importance for models that support it \n",
|
|
" def show_feature_importance(self):\n",
|
|
" importance = {}\n",
|
|
" features = self.feature_names\n",
|
|
"\n",
|
|
" for name, result in self.models.items():\n",
|
|
" model = result['model']\n",
|
|
" if hasattr(model, 'feature_importances_'):\n",
|
|
" importance[name] = model.feature_importances_\n",
|
|
" elif hasattr(model, 'coef_'):\n",
|
|
" coef = model.coef_\n",
|
|
" if coef.ndim == 1:\n",
|
|
" importance[name] = np.abs(coef)\n",
|
|
" else:\n",
|
|
" importance[name] = np.mean(np.abs(coef), axis=0)\n",
|
|
" else:\n",
|
|
" print(f\"Feature importance not available for model {name}\")\n",
|
|
"\n",
|
|
" for name, imp in importance.items():\n",
|
|
" sorted_idx = np.argsort(imp)[::-1]\n",
|
|
" sorted_features = [features[i] for i in sorted_idx]\n",
|
|
" plt.figure()\n",
|
|
" plt.bar(range(len(imp)), imp[sorted_idx], align='center')\n",
|
|
" plt.xticks(range(len(imp)), sorted_features, rotation=70)\n",
|
|
" plt.title(f\"Feature importance for {name}\")\n",
|
|
" plt.xlabel(\"Feature index\")\n",
|
|
" plt.ylabel(\"Importance score\")\n",
|
|
" plt.grid(True, linestyle='--', alpha=0.6)\n",
|
|
" plt.show()\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "da377fc1",
|
|
"metadata": {},
|
|
"source": [
|
|
"### Compare models with coarse hyperparameter tuning"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 8,
|
|
"id": "d6fd1fee",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Tuning Decision Tree ...\n",
|
|
"Tuning Random Forest ...\n",
|
|
"Tuning XGBoost ...\n",
|
|
"\n",
|
|
"------ Results Sorted by Accuracy ------\n",
|
|
" Model Accuracy Precision Recall F1 Score Best Params Training Time (s) Prediction Time (s) Total Time (s)\n",
|
|
" XGBoost 0.868059 0.863590 0.868059 0.863957 {'learning_rate': 0.2, 'max_depth': 5, 'n_estimators': 100} 30.477441 0.007370 30.484811\n",
|
|
"Random Forest 0.858942 0.853479 0.858942 0.853443 {'max_depth': 20, 'min_samples_split': 10, 'n_estimators': 100} 109.089292 0.072799 109.162091\n",
|
|
"Decision Tree 0.848334 0.844900 0.848334 0.846228 {'max_depth': 10, 'min_samples_split': 5} 10.185913 0.002266 10.188179\n",
|
|
"\n",
|
|
"------ Results Sorted by Total Time ------\n",
|
|
" Model Accuracy Precision Recall F1 Score Best Params Training Time (s) Prediction Time (s) Total Time (s)\n",
|
|
"Decision Tree 0.848334 0.844900 0.848334 0.846228 {'max_depth': 10, 'min_samples_split': 5} 10.185913 0.002266 10.188179\n",
|
|
" XGBoost 0.868059 0.863590 0.868059 0.863957 {'learning_rate': 0.2, 'max_depth': 5, 'n_estimators': 100} 30.477441 0.007370 30.484811\n",
|
|
"Random Forest 0.858942 0.853479 0.858942 0.853443 {'max_depth': 20, 'min_samples_split': 10, 'n_estimators': 100} 109.089292 0.072799 109.162091\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"# optimized classifiers and find their hyperparameters\n",
|
|
"clf_opt = ClassifierComparisonOpt(X_train_val, y_train_val)\n",
|
|
"clf_opt.fit_models()\n",
|
|
"clf_opt.print_summary()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "dc529395",
|
|
"metadata": {},
|
|
"source": [
|
|
"### Finetune and compare again\n",
|
|
"After tuning with a coarse grid we can use the result to select a finer grid and find better hyperparameters. This will only slightly improve the models, you will generally get diminishing returns the finer you tune."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 5,
|
|
"id": "4185a428",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# Define the classifiers and their hyperparameters in a finer grid\n",
|
|
"def get_fine_grids(use_bootstrap=True):\n",
|
|
" return {\n",
|
|
" 'Decision Tree': (DecisionTreeClassifier(random_state=42), {\n",
|
|
" 'max_depth': [8, 10, 12],\n",
|
|
" 'min_samples_split': [4, 5, 6],\n",
|
|
" }),\n",
|
|
" 'Random Forest': (RandomForestClassifier(bootstrap=use_bootstrap, random_state=42, n_jobs=-1), {\n",
|
|
" 'n_estimators': [75, 100, 150], \n",
|
|
" 'max_depth': [15, 20, 25],\n",
|
|
" 'min_samples_split': [8, 10, 12],\n",
|
|
" }),\n",
|
|
" 'XGBoost': (XGBClassifier(eval_metric='mlogloss', random_state=42, n_jobs=-1), {\n",
|
|
" 'n_estimators': [75, 100, 150],\n",
|
|
" 'learning_rate': [0.15, 0.2, 0.25],\n",
|
|
" 'max_depth': [4, 5, 6]\n",
|
|
" })\n",
|
|
" }\n",
|
|
"\n",
|
|
"# optimized classifiers and find their hyperparameters\n",
|
|
"#clf_opt = ClassifierComparisonOpt(X_train_val, y_train_val)\n",
|
|
"fine_grid = get_fine_grids()\n",
|
|
"#clf_opt.fit_models(fine_grid)\n",
|
|
"#clf_opt.print_summary()\n",
|
|
"\n",
|
|
"# Show feature importance for each model\n",
|
|
"#clf_opt.show_feature_importance()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "01f5866d",
|
|
"metadata": {},
|
|
"source": [
|
|
"### Remove redundant features (optional)\n",
|
|
"If we want to remove redundant features, we will have to select different features for different models as the importance scores varied slightly between models. However, we have kept this section optional since we may want to use the same feature sets for all models in order to produce a fair comparison. Nevertheless, for optimal performance of each model, this step is advantageous."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 4,
|
|
"id": "776cdb17",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"ename": "NameError",
|
|
"evalue": "name 'fine_grid' is not defined",
|
|
"output_type": "error",
|
|
"traceback": [
|
|
"\u001b[31m---------------------------------------------------------------------------\u001b[39m",
|
|
"\u001b[31mNameError\u001b[39m Traceback (most recent call last)",
|
|
"\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[4]\u001b[39m\u001b[32m, line 10\u001b[39m\n\u001b[32m 8\u001b[39m \u001b[38;5;66;03m# Train decision tree without redundant features\u001b[39;00m\n\u001b[32m 9\u001b[39m cmp_dt = ClassifierComparisonOpt(X_dt, y_train_val)\n\u001b[32m---> \u001b[39m\u001b[32m10\u001b[39m cmp_dt.fit_models({\u001b[33m'\u001b[39m\u001b[33mDecision Tree\u001b[39m\u001b[33m'\u001b[39m: \u001b[43mfine_grid\u001b[49m[\u001b[33m'\u001b[39m\u001b[33mDecision Tree\u001b[39m\u001b[33m'\u001b[39m]})\n\u001b[32m 12\u001b[39m \u001b[38;5;66;03m# Train XGBoost without redundant features\u001b[39;00m\n\u001b[32m 13\u001b[39m cmp_xgb = ClassifierComparisonOpt(X_xgb, y_train_val)\n",
|
|
"\u001b[31mNameError\u001b[39m: name 'fine_grid' is not defined"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"# Remove redundant features for decision tree\n",
|
|
"X_dt = X_train_val.drop(columns=['sex', 'native.country', 'marital.status', 'race', 'occupation', 'workclass'])\n",
|
|
"\n",
|
|
"# Remove redundant features for XGBoost\n",
|
|
"X_xgb = X_train_val.drop(columns=['native.country', 'race'])\n",
|
|
"\n",
|
|
"\n",
|
|
"# Train decision tree without redundant features\n",
|
|
"cmp_dt = ClassifierComparisonOpt(X_dt, y_train_val)\n",
|
|
"cmp_dt.fit_models({'Decision Tree': fine_grid['Decision Tree']})\n",
|
|
"\n",
|
|
"# Train XGBoost without redundant features\n",
|
|
"cmp_xgb = ClassifierComparisonOpt(X_xgb, y_train_val)\n",
|
|
"cmp_xgb.fit_models({'XGBoost': fine_grid['XGBoost']})\n",
|
|
"\n",
|
|
"# Train Random Forest, keep all features\n",
|
|
"cmp_rf = ClassifierComparisonOpt(X_train_val, y_train_val)\n",
|
|
"cmp_rf.fit_models({'Random Forest': fine_grid['Random Forest']})\n",
|
|
"\n",
|
|
"\n",
|
|
"# Print results\n",
|
|
"res = pd.concat([cmp_dt.results_df, cmp_rf.results_df, cmp_xgb.results_df])\n",
|
|
"print(\"\\n------ Results Sorted by Accuracy ------\")\n",
|
|
"print(res.sort_values(by='Accuracy', ascending=False).to_string(index=False))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "6fbac4c8",
|
|
"metadata": {},
|
|
"source": [
|
|
"### Final Models\n",
|
|
"I have not run this code yet. I'm still not sure if we should remove some of the features."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 12,
|
|
"id": "a470fd20",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Classification Report:\n",
|
|
" precision recall f1-score support\n",
|
|
"\n",
|
|
" Poor 0.87 0.95 0.90 4533\n",
|
|
" Rich 0.77 0.56 0.65 1500\n",
|
|
"\n",
|
|
" accuracy 0.85 6033\n",
|
|
" macro avg 0.82 0.75 0.78 6033\n",
|
|
"weighted avg 0.84 0.85 0.84 6033\n",
|
|
"\n"
|
|
]
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 640x480 with 2 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
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"Classification Report:\n",
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|
" precision recall f1-score support\n",
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"\n",
|
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" Poor 0.89 0.94 0.91 4533\n",
|
|
" Rich 0.77 0.63 0.70 1500\n",
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"\n",
|
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" accuracy 0.86 6033\n",
|
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" macro avg 0.83 0.79 0.80 6033\n",
|
|
"weighted avg 0.86 0.86 0.86 6033\n",
|
|
"\n"
|
|
]
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 640x480 with 2 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Classification Report:\n",
|
|
" precision recall f1-score support\n",
|
|
"\n",
|
|
" Poor 0.89 0.94 0.91 4533\n",
|
|
" Rich 0.77 0.66 0.71 1500\n",
|
|
"\n",
|
|
" accuracy 0.87 6033\n",
|
|
" macro avg 0.83 0.80 0.81 6033\n",
|
|
"weighted avg 0.86 0.87 0.86 6033\n",
|
|
"\n"
|
|
]
|
|
},
|
|
{
|
|
"data": {
|
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"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 640x480 with 2 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"# ---------------------------- Decision Tree ----------------------------\n",
|
|
"dt = Pipeline([\n",
|
|
" ('dt', DecisionTreeClassifier(max_depth=8, min_samples_split=4, random_state=42)) \n",
|
|
"])\n",
|
|
"\n",
|
|
"# Train the model\n",
|
|
"dt.fit(X_train_val, y_train_val)\n",
|
|
"y_pred_dt = dt.predict(X_test)\n",
|
|
"\n",
|
|
"# Classification Report\n",
|
|
"print(\"Classification Report:\")\n",
|
|
"print(classification_report(y_test, y_pred_dt, target_names=[\"Poor\", \"Rich\"]))\n",
|
|
"\n",
|
|
"CM = confusion_matrix(y_test, y_pred_dt)\n",
|
|
"disp = ConfusionMatrixDisplay(confusion_matrix=CM, display_labels=[\"Poor\", \"Rich\"])\n",
|
|
"disp.plot(cmap=\"Blues\")\n",
|
|
"plt.title(\"Confusion Matrix (dt)\")\n",
|
|
"plt.savefig('./Report/CM_dt.png', format='png', dpi=300)\n",
|
|
"plt.show() \n",
|
|
"\n",
|
|
"\n",
|
|
"# ---------------------------- Random Forest ----------------------------\n",
|
|
"rf = Pipeline([\n",
|
|
" ('rf', RandomForestClassifier(max_depth=20, min_samples_split=10, n_estimators=100, bootstrap=True, random_state=42))\n",
|
|
"])\n",
|
|
"\n",
|
|
"# Train the model\n",
|
|
"rf.fit(X_train_val, y_train_val)\n",
|
|
"y_pred_rf = rf.predict(X_test)\n",
|
|
"\n",
|
|
"# Classification Report\n",
|
|
"print(\"Classification Report:\")\n",
|
|
"print(classification_report(y_test, y_pred_rf, target_names=[\"Poor\", \"Rich\"]))\n",
|
|
"\n",
|
|
"CM = confusion_matrix(y_test, y_pred_rf)\n",
|
|
"disp = ConfusionMatrixDisplay(confusion_matrix=CM, display_labels=[\"Poor\", \"Rich\"])\n",
|
|
"disp.plot(cmap=\"Blues\")\n",
|
|
"plt.title(\"Confusion Matrix Random Forest\")\n",
|
|
"plt.savefig('./Report/CM_rf.png', format='png', dpi=300)\n",
|
|
"plt.show() \n",
|
|
"\n",
|
|
"\n",
|
|
"# ---------------------------- XGBoost ----------------------------\n",
|
|
"xgb = Pipeline([\n",
|
|
" ('xgb', XGBClassifier(learning_rate=0.15, max_depth=5, n_estimators=100, random_state=42))\n",
|
|
"])\n",
|
|
"\n",
|
|
"# Train the model\n",
|
|
"xgb.fit(X_train_val, y_train_val)\n",
|
|
"y_pred_xgb = xgb.predict(X_test)\n",
|
|
"\n",
|
|
"# Classification Report\n",
|
|
"print(\"Classification Report:\")\n",
|
|
"print(classification_report(y_test, y_pred_xgb, target_names=[\"Poor\", \"Rich\"]))\n",
|
|
"\n",
|
|
"CM = confusion_matrix(y_test, y_pred_xgb)\n",
|
|
"disp = ConfusionMatrixDisplay(confusion_matrix=CM, display_labels=[\"Poor\", \"Rich\"])\n",
|
|
"disp.plot(cmap=\"Blues\")\n",
|
|
"plt.title(\"Confusion Matrix XGBoost\")\n",
|
|
"plt.savefig('./Report/CM_xgb.png', format='png', dpi=300)\n",
|
|
"plt.show() "
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": ".venv",
|
|
"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": "3.12.12"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|