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| <head> | |
| <title>GENE_FAMILY: GRF</title> | |
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| body { font-family: Arial, sans-serif; } | |
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| .title { padding: 0.6em; background-color: #80c4e6bd; font-weight: bold; } | |
| .section { padding: 10px; } | |
| .metrics { display: flex; } | |
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| .metrics ul + ul { margin-left: 2em; } | |
| .confusion-matrix img, .learning-curve img { width: 100%; max-width: 565px; } | |
| .class_dist { width: 20em; } | |
| .mod_sum { margin-bottom: 2em; } | |
| </style> | |
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| <body> | |
| <div class="container title"> | |
| <h3>GENE_FAMILY: <a href='https://planttfdb.gao-lab.org/family.php?fam=GRF' target='_blank'>GRF</a></h3> | |
| </div> | |
| <div class="container"> | |
| <div class="header">MODEL: FEEDFORWARD_k2</div> | |
| <div style="display: flex;"> | |
| <div class="section"> | |
| <h2 class='mod_sum'>Model Architecture</h2> | |
| <pre>Model: "FEEDFORWARD_k2" | |
| ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓ | |
| ┃ Layer (type) ┃ Output Shape ┃ Param # ┃ | |
| ┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩ | |
| │ dense (Dense) │ (None, 256) │ 113,152 │ | |
| ├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤ | |
| │ dropout (Dropout) │ (None, 256) │ 0 │ | |
| ├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤ | |
| │ dense_1 (Dense) │ (None, 128) │ 32,896 │ | |
| ├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤ | |
| │ dropout_1 (Dropout) │ (None, 128) │ 0 │ | |
| ├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤ | |
| │ dense_2 (Dense) │ (None, 64) │ 8,256 │ | |
| ├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤ | |
| │ dropout_2 (Dropout) │ (None, 64) │ 0 │ | |
| ├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤ | |
| │ dense_3 (Dense) │ (None, 32) │ 2,080 │ | |
| ├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤ | |
| │ dropout_3 (Dropout) │ (None, 32) │ 0 │ | |
| ├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤ | |
| │ dense_4 (Dense) │ (None, 1) │ 33 │ | |
| └──────────────────────────────────────┴─────────────────────────────┴─────────────────┘ | |
| Total params: 469,253 (1.79 MB) | |
| Trainable params: 156,417 (611.00 KB) | |
| Non-trainable params: 0 (0.00 B) | |
| Optimizer params: 312,836 (1.19 MB) | |
| </pre> | |
| </div> | |
| <div class="section learning-curve"> | |
| <h2>Learning Curve</h2> | |
| <img 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" alt="Learning Curve"> | |
| </div> | |
| </div> | |
| <div style="display: flex;"> | |
| <div class="section class_dist"> | |
| <h2>Class Distribution</h2> | |
| <pre> Count Percentage | |
| class | |
| 1 1876 50.35 | |
| 0 1850 49.65</pre> | |
| <h3>Additional Metrics</h3> | |
| <ul> | |
| <li>Total Samples: 3726</li> | |
| <li>Imbalance Ratio: 1.01</li> | |
| </ul> | |
| </div> | |
| <div class="section"> | |
| <h2>Classification Report</h2> | |
| <pre> precision recall f1-score support | |
| Class 0 0.9973 0.9946 0.9959 370 | |
| Class 1 0.9947 0.9973 0.9960 376 | |
| accuracy 0.9960 746 | |
| macro avg 0.9960 0.9960 0.9960 746 | |
| weighted avg 0.9960 0.9960 0.9960 746 | |
| </pre> | |
| <h3>Metrics</h3> | |
| <div class="metrics"> | |
| <ul> | |
| <li>True Positives (TP): 375</li> | |
| <li>True Negatives (TN): 368</li> | |
| </ul> | |
| <ul> | |
| <li>False Positives (FP): 2</li> | |
| <li>False Negatives (FN): 1</li> | |
| </ul> | |
| </div> | |
| </div> | |
| <div class="section confusion-matrix"> | |
| <h2>Confusion Matrix</h2> | |
| <img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAlgAAAGQCAYAAAByNR6YAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8fJSN1AAAACXBIWXMAAA9hAAAPYQGoP6dpAAA9GUlEQVR4nO3de1iUdf7/8ddwGjkrHhhQMg20TCrTUtRVPJ/QTDc129LN+pGpxRfNVkulzUStxPJUXysty9XStDYPqZm6xtfymHgoT5iZIFqESji4eP/+cJ1tQguZGwaH52Ov+7rkvj/3zPtm59JX78/nvsdiGIYhAAAAmMbL3QUAAAB4GgIWAACAyQhYAAAAJiNgAQAAmIyABQAAYDICFgAAgMkIWAAAACYjYAEAAJiMgAUAAGAyAhYAAIDJCFgAAAAmI2ABAACYjIAFAABgMgIWAACAyQhYAAAAJiNgAQAAmIyABQAAYDICFgAAgMkIWAAAACYjYAEAAJiMgAUAAGAyAhYAAIDJCFgAAAAmI2ABAACYjIAFAABgMgIWAACAyQhYAAAAJiNgAQAAmIyABQAAYDICFgAAgMkIWAAAACYjYAEAAJiMgAUAAGAyAhYAAIDJCFgAAAAmI2ABAACYjIAFAABgMgIWAACAyQhYAAAAJiNgAQAAmIyABQAAYDICFgAAgMkIWAAAACYjYAEAAJiMgAUAAGAyAhYAAIDJCFgAAAAm83F3AdeTJO9Qd5cAlLnpZ4+5uwSg7AWU3d/nj1lCXDr/NeOMSZXAnQhYAACYiKkhSAQsAABM5WWxuLsEVAAEbQAAAJPRwQIAwER0LiARsAAAMJUXM4QQAQsAAFPRwYJEwAIAwFQscodEwAIAwFR0sCDxOQAAADAdHSwAAEzEIndIBCwAAEzF1BAkAhYAAKaysMgdImABAGAqOliQCFgAAJiKNViQCNoAAACmI2ABAGAiLxe3kpozZ45uu+02hYSEKCQkRHFxcVq1apXj+ODBg2WxWJy2Fi1aOL2G3W7XiBEjVKNGDQUGBqpXr146fvx4aS8dv0LAAgDARF4Wi0tbSdWpU0eTJ0/Wtm3btG3bNrVv31733HOP9u7d6xjTtWtXZWVlObaVK1c6vUZSUpKWLVumRYsWafPmzTp37pwSEhJUVFRk2u+jsmINFgAAJiqvzkXPnj2dfn7hhRc0Z84cbdmyRbfeeqskyWq1ymazXfH8vLw8vfnmm1qwYIE6duwoSXr33XcVFRWldevWqUuXLmV7AR6ODhYAACbysri2lUZRUZEWLVqk/Px8xcXFOfZv2LBBtWrVUoMGDfToo48qJyfHcWz79u26cOGCOnfu7NgXGRmpxo0bKz09vdTXj0voYAEAYCJXOxd2u112u91pn9VqldVqLTY2IyNDcXFxOn/+vIKCgrRs2TI1atRIktStWzfdd999qlu3rjIzMzVu3Di1b99e27dvl9VqVXZ2tvz8/FStWjWn1wwPD1d2draLVwE6WAAAVCCpqakKDQ112lJTU684tmHDhtq1a5e2bNmioUOHatCgQdq3b58kqX///urRo4caN26snj17atWqVTpw4IBWrFjxu+9vGAYPSzUBHSwAAEzkJdfCyZgxY5ScnOy070rdK0ny8/NTdHS0JKlZs2baunWrXnnlFb3++uvFxkZERKhu3bo6ePCgJMlms6mwsFC5ublOXaycnBy1bNnSpWsAHSwAAEzl6hosq9XqePTC5e1qAeu3DMMoNr142Y8//qjvv/9eERERkqSmTZvK19dXa9eudYzJysrSnj17CFgmoIMFAICJyqtzMXbsWHXr1k1RUVE6e/asFi1apA0bNmj16tU6d+6cUlJS1LdvX0VEROjo0aMaO3asatSooXvvvVeSFBoaqiFDhmjkyJGqXr26wsLCNGrUKMXGxjruKkTpEbAAADBReX1VzsmTJ/Xggw8qKytLoaGhuu2227R69Wp16tRJBQUFysjI0DvvvKOff/5ZERERateunRYvXqzg4GDHa6SlpcnHx0f9+vVTQUGBOnTooPnz58vb27t8LsKDWQzDMNxdxPUiyTvU3SUAZW762WPuLgEoewFl9/f5jMAaLp0/Iv+0SZXAnViDBQAAYDKmCAEAMFF5TRGiYiNgAQBgIqaGIBGwAAAwFR0sSAQsAABM5eqDRuEZCFgAAJiIDhYkpooBAABMRwcLAAAT0cCCRMACAMBUTBFCImABAGAqFrlDImABAGAqOliQWOQOAABgOjpYAACYiM4FJAIWAACmYoYQEgELAABTeVmIWCBgAQBgKuIVJAIWAACmImBBYi0eAACA6ehgAQBgIjpYkAhYAACYysIid4iABQCAqYhXkAhYAACYisXNkAhYAACYihlCSARtAAAA09HBAgDARBZWYUEELAAATEW8gkTAAgDAVAQsSB4YsPLz87Vw4UKlp6crOztbFotF4eHhatWqle6//34FBga6u0QAgAfzImFBHrbIfd++fWrQoIFGjx6t3Nxc3XDDDapTp45yc3P11FNPqWHDhtq3b5+7ywQAeDCLi/+DZ/CoDtawYcPUpk0bvf322/Lz83M6VlhYqMGDB2vYsGH6/PPP3VQhAACoDDyqg/Xll19q3LhxxcKVJPn5+Wns2LH68ssv3VAZAKCysLi4ldScOXN02223KSQkRCEhIYqLi9OqVascxw3DUEpKiiIjI+Xv76/4+Hjt3bvX6TXsdrtGjBihGjVqKDAwUL169dLx48dLe+n4FY8KWNWqVdPBgwevevzQoUOqVq1aOVYEAKhsLBbXtpKqU6eOJk+erG3btmnbtm1q37697rnnHkeImjp1qqZNm6aZM2dq69atstls6tSpk86ePet4jaSkJC1btkyLFi3S5s2bde7cOSUkJKioqMjsX0ulYzEMw3B3EWZJSUnR9OnT9eyzz6pTp04KDw+XxWJRdna21q5dq0mTJikpKUnjx48v1esneYeaXDFQ8Uw/e8zdJQBlL6Ds/j5fUzPSpfM7nzpR6nPDwsL04osv6uGHH1ZkZKSSkpL09NNPS7rUrQoPD9eUKVOUmJiovLw81axZUwsWLFD//v0lSSdOnFBUVJRWrlypLl26uHQdlZ1HrcFKSUmRv7+/pk2bptGjRzu+0dwwDNlsNv3tb3/T6NGj3VwlAMCTeblhoXpRUZE++OAD5efnKy4uTpmZmcrOzlbnzp0dY6xWq9q2bav09HQlJiZq+/btunDhgtOYyMhINW7cWOnp6QQsF3lUwJKkp59+Wk8//bTjwyVJNptN9erVc3NlAIDKwNV4ZbfbZbfbnfZZrVZZrdZiYzMyMhQXF6fz588rKChIy5YtU6NGjZSeni5JCg8PdxofHh6u7777TpKUnZ0tPz+/YktnwsPDHf9+ovQ8ag3Wr9WrV09xcXGKi4sjXAEArhupqakKDQ112lJTU684tmHDhtq1a5e2bNmioUOHatCgQU6PI7L8ZlGXYRjF9v1WScbgj3lcBwsAAHdyNZuMGTNGycnJTvuu1L2SLt0hHx0dLUlq1qyZtm7dqldeecWx7io7O1sRERGO8Tk5OY6uls1mU2FhoXJzc526WDk5OWrZsqVrFwHP7WABAOAOrj6mwWq1Oh69cHm7WsD6LcMwZLfbVa9ePdlsNq1du9ZxrLCwUBs3bnSEp6ZNm8rX19dpTFZWlvbs2UPAMgEdLAAATFReT2MfO3asunXrpqioKJ09e1aLFi3Shg0btHr1alksFiUlJWnSpEmKiYlRTEyMJk2apICAAA0cOFCSFBoaqiFDhmjkyJGqXr26wsLCNGrUKMXGxqpjx47lcg2ejIAFAICJyuu7CE+ePKkHH3xQWVlZCg0N1W233abVq1erU6dOkqTRo0eroKBAjz/+uHJzc9W8eXOtWbNGwcHBjtdIS0uTj4+P+vXrp4KCAnXo0EHz58+Xt7d3+VyEB/Oo52Bdtnr1agUFBal169aSpFmzZmnu3Llq1KiRZs2aVeqHjfIcLFQGPAcLlUIZPgfrX+F1XDr/Tyd5kron8Mg1WE899ZTOnDkj6dItrCNHjlT37t115MiRYgsHAQAAzOaRU4SZmZlq1KiRJGnp0qVKSEjQpEmTtGPHDnXv3t3N1QEAPBkPOIDkoR0sPz8//fLLL5KkdevWOZ5SGxYW5uhsAQBQFiwu/g+ewSM7WK1bt1ZycrJatWqlr776SosXL5YkHThwQHXquDY3Dte0emyIWiU+rLAbb5AkZe/9Rp9OnKL9q9c5xoTf3EA9Jz+nm9q0ksXLS9l7v9H8AYP18/eX1iUEh9dSr6nPq2HHdrIGBynn20NaN/llfb30I7dcE1Aar785X2vWf64jR79TFatVTW6P1agnR6j+jXXdXRpcxDM6IXloB2vmzJny8fHRkiVLNGfOHNWuXVuStGrVKnXt2tXN1VVuPx//Qf8cm6KX747Xy3fH68DnmzRk2T9ka3SzJKl6/Xp6YtOnOvnNQc1sn6AXm7TWmhem6t/nzzte4y/v/K9qNYjRG70HaOrtLbV72cca9I95qn3Hbe66LOCafbVjhx7of5/ef+dNzZszQ0VFRRoydIR+KShwd2lwkZeLGzyDR95FWFa4i7BsvHDqqD5+epy+fGuBHlr4loouXNB7gxKvOn5K3g/6YFiytr27+L+vkZOpj/82Xl++taA8SvZo3EXoHj/9lKu4Dl307huv6a6md7q7HM9XhncRfmmLcun85tnfm1QJ3Mkjw/KOHTuUkZHh+Pmjjz5S7969NXbsWBUWFrqxMvyaxctLTfr3lTUwQEf/7ytZLBY16t5Zpw4c0mOrPtTzWYf0P+mfKfaeHk7nHflii5r066OAatVksVjUpH9f+Vj9dGjDZjddCeC6s+fOSbr08EcA1z+PDFiJiYk6cOCAJOnIkSMaMGCAAgIC9MEHH2j06NFurg4RjRtpSt4PeqnglPrNnqY3+z6gk/u/VVCtmqoSHKwOT/+P9q9ep9e63qvdyz/RX5e8q5vatHKc//aAv8rLx0eTTh+99Bpz0vRm37/oxyOZbrwqoPQMw1Dqy9PVtMntahB9k7vLgYssFotLGzyDRy5yP3DggO644w5J0gcffKA2bdpo4cKF+uKLLzRgwABNnz79D1/DbrfLbrc77fu3YciHD7/Lcr49qBfv/JP8q4bq9j699MC81zSjXXcV/JwnSdrz8UptfGW2JOmHrzNUr+XdapX4sA5v+kKS1P35ZxVQtapmdeql/NM/KvaeHvrr4vl6tW03Ze3Zd9X3BSqqv09+UQcOHtLCef/r7lJgAv6VgOShHSzDMHTx4kVJlx7TcPnZV1FRUTp9+nSJXiM1NVWhoaFO2zbD/scn4g8VXbig04eP6PvtO/XJM8/ph6/3qO0TQ5V/+kcVXbig7H3fOI0/uf+AqkZduvuzev16ajM8Uf94ZJgOrt+oE7v36NPnp+jYtl1q/fij7rgcwCXPT35R6zdu0ttzZ8sWHu7ucmACV7/sGZ7BIwNWs2bNNHHiRC1YsEAbN25Ujx6X1vBkZmYqvIR/gY0ZM0Z5eXlOWzNLyb7NHNfGYrHIx+qnogsXdGzrDtVqGON0vGaDm5R77NKiT78Af0mS8Z8AfZlxsUgWL4/8OMNDGYahv09+UWvWb9Dbr89W1H/udsb1jylCSB46RTh9+nQ98MADWr58uZ555hlFR0dLkpYsWaKWLVuW6DWsVqusVudAxfSg63pMHK/9q9fq5+9/kDU4SE3691V0fGu91r2vJGn9y69q0D/m6fC/0nXo83/p5i4ddGtCN81sfykkn/zmgE4dPKx+c6bro9HPKv/HXMXe00MNOrbT3F793HlpwDV5LnWqPln1qWanvaTAwACd+k93PTgoSFWqVHFzdXBFeX3ZMyq2SvWYhvPnz8vb21u+vr6lOp/HNLhuwNyZatC+jUIibCrIO6MTu/fqsxen68C6zx1jmv/1L+r4dLJC60Tq1LcHteq5VO35eKXjeI3o+uqZ+pzqt2ohv6BAnT50RJ9Pm+H02AaUHo9pKB8Nm9x9xf2pz41Xn14J5VxNJVSGj2nYWdu1h8U2+eE7kyqBO1WqgOUqAhYqAwIWKoUyDFi7om506fw7vj9qSh1wL4+cIiwqKlJaWpref/99HTt2rNizr3766Sc3VQYA8HSsJoHkoYvcn3vuOU2bNk39+vVTXl6ekpOT1adPH3l5eSklJcXd5QEAPJjF4toGz+CRAeu9997T3LlzNWrUKPn4+Oj+++/XG2+8ofHjx2vLli3uLg8A4MG4ixCShwas7OxsxcbGSpKCgoKUl3fpAZYJCQlasWKFO0sDAHg4OliQPDRg1alTR1lZWZKk6OhorVmzRpK0devWYo9eAAAAMJtHBqx7771Xn332mSTpySef1Lhx4xQTE6OHHnpIDz/8sJurAwB4MqYIIXnoXYSTJ092/PnPf/6z6tSpo/T0dEVHR6tXr15urAwA4OnISJA8NGD9VosWLdSiRQt3lwEAqAS8SFiQBwWsjz/+uMRj6WIBAMoK+QqSBwWs3r17l2icxWJRUVFR2RYDAKi0WEcFyYMC1sWLF91dAgAAgCQPClgAAFQEFo+8Px/XyqM+BuvXr1ejRo105syZYsfy8vJ06623atOmTW6oDABQWfCYBkgeFrCmT5+uRx99VCEhIcWOhYaGKjExUWlpaW6oDABQWfAkd0geFrC+/vprde3a9arHO3furO3bt5djRQCAyoYOFiQPW4N18uRJ+fr6XvW4j4+PTp06VY4VAQAqGzISJA/rYNWuXVsZGRlXPb57925FRESUY0UAAJSN1NRU3XXXXQoODlatWrXUu3dvffvtt05jBg8eXKxD9tsHb9vtdo0YMUI1atRQYGCgevXqpePHj5fnpXgkjwpY3bt31/jx43X+/PlixwoKCjRhwgQlJCS4oTIAQGXhZbG4tJXUxo0bNWzYMG3ZskVr167Vv//9b3Xu3Fn5+flO47p27aqsrCzHtnLlSqfjSUlJWrZsmRYtWqTNmzfr3LlzSkhI4JmRLrIYhmG4uwiznDx5Unfeeae8vb01fPhwNWzYUBaLRfv379esWbNUVFSkHTt2KDw8vFSvn+QdanLFQMUz/ewxd5cAlL2Asvv7/NhtDV06/4bd3/7xoCs4deqUatWqpY0bN6pNmzaSLnWwfv75Zy1fvvyK5+Tl5almzZpasGCB+vfvL0k6ceKEoqKitHLlSnXp0qVUtcDD1mCFh4crPT1dQ4cO1ZgxY3Q5O1osFnXp0kWzZ88udbgCAKAk3LVQPS8vT5IUFhbmtH/Dhg2qVauWqlatqrZt2+qFF15QrVq1JEnbt2/XhQsX1LlzZ8f4yMhINW7cWOnp6QQsF3hUwJKkunXrauXKlcrNzdWhQ4dkGIZiYmJUrVo1d5cGAKgEXM1XdrtddrvdaZ/VapXVar3qOYZhKDk5Wa1bt1bjxo0d+7t166b77rtPdevWVWZmpsaNG6f27dtr+/btslqtys7Olp+fX7F/I8PDw5Wdne3ahVRyHhewLqtWrZruuusud5cBAKhkXA1Yqampeu6555z2TZgwQSkpKVc9Z/jw4dq9e7c2b97stP/ytJ8kNW7cWM2aNVPdunW1YsUK9enT56qvZxgGj4xwkccGLAAArkdjxoxRcnKy077f616NGDFCH3/8sTZt2qQ6der87mtHRESobt26OnjwoCTJZrOpsLBQubm5Tl2snJwctWzZ0oWrgEfdRQgAgLtZvCwubVarVSEhIU7blQKWYRgaPny4PvzwQ61fv1716tX7w9p+/PFHff/9945HFjVt2lS+vr5au3atY0xWVpb27NlDwHIRHSwAAExUXjNrw4YN08KFC/XRRx8pODjYsWYqNDRU/v7+OnfunFJSUtS3b19FRETo6NGjGjt2rGrUqKF7773XMXbIkCEaOXKkqlevrrCwMI0aNUqxsbHq2LFj+VyIhyJgAQBgomt5lpUr5syZI0mKj4932j9v3jwNHjxY3t7eysjI0DvvvKOff/5ZERERateunRYvXqzg4GDH+LS0NPn4+Khfv34qKChQhw4dNH/+fHl7e5fLdXgqj3oOVlnjOVioDHgOFiqFMnwOVs7djVw6v9ZX+0yqBO5EBwsAABNx9x0kFrkDAACYjg4WAAAmooEFiYAFAICpmCKERMACAMBU5CtIBCwAAExFBwsSi9wBAABMRwcLAAATWWhdQAQsAABMxRQhJAIWAADm8iJggYAFAIC56GBBBCwAAEzFFCEk7iIEAAAwHR0sAADMxBosiIAFAIC5mCKECFgAAJjKQgcLImABAGAuOlgQAQsAAFPRwYLEXYQAAACmo4MFAICZmCKECFgAAJiLKUKIgAUAgKl4kjskAhYAAOaigwURsAAAMBcdLIi7CAEAAExHBwsAABNZaF1Abg5YH3/8cYnH9urVqwwrAQDAJEwRQm4OWL179y7ROIvFoqKiorItBgAAE/Akd0huDlgXL15059sDAGA+OlgQa7AAADAXHSyoggWs/Px8bdy4UceOHVNhYaHTsSeeeMJNVQEAAFybCnOvw86dOxUdHa37779fw4cP18SJE5WUlKSxY8dq+vTp7i4PAIASsVgsLm0llZqaqrvuukvBwcGqVauWevfurW+//dZpjGEYSklJUWRkpPz9/RUfH6+9e/c6jbHb7RoxYoRq1KihwMBA9erVS8ePHzfld1GZVZiA9T//8z/q2bOnfvrpJ/n7+2vLli367rvv1LRpU7300kvuLg8AgJLxsri2ldDGjRs1bNgwbdmyRWvXrtW///1vde7cWfn5+Y4xU6dO1bRp0zRz5kxt3bpVNptNnTp10tmzZx1jkpKStGzZMi1atEibN2/WuXPnlJCQwM1lLrIYhmG4uwhJqlq1qr788ks1bNhQVatW1f/93//plltu0ZdffqlBgwbpm2++cXeJSvIOdXcJQJmbfvaYu0sAyl5A2f19fv7B9i6dX2XB+lKdd+rUKdWqVUsbN25UmzZtZBiGIiMjlZSUpKefflrSpW5VeHi4pkyZosTEROXl5almzZpasGCB+vfvL0k6ceKEoqKitHLlSnXp0sWla6nMKkwHy9fX19EaDQ8P17Fjl/6SDw0NdfwZAICKztUpQrvdrjNnzjhtdrv9D983Ly9PkhQWFiZJyszMVHZ2tjp37uwYY7Va1bZtW6Wnp0uStm/frgsXLjiNiYyMVOPGjR1jUDoVJmA1adJE27ZtkyS1a9dO48eP13vvvaekpCTFxsa6uToAAErIxSnC1NRUhYaGOm2pqam/+5aGYSg5OVmtW7dW48aNJUnZ2dmSLjUtfi08PNxxLDs7W35+fqpWrdpVx6B0KsxdhJMmTXLMCT///PMaNGiQhg4dqujoaM2bN8/N1QEAUD7GjBmj5ORkp31Wq/V3zxk+fLh2796tzZs3Fzv224XzhmH84WL6kozB76swAatZs2aOP9esWVMrV650YzUAAJSOq8HEz2r9w0D1ayNGjNDHH3+sTZs2qU6dOo79NptN0qUuVUREhGN/Tk6Oo6tls9lUWFio3Nxcpy5WTk6OWrZs6dJ1VHYVZooQAACPUE53ERqGoeHDh+vDDz/U+vXrVa9ePafj9erVk81m09q1ax37CgsLtXHjRkd4atq0qXx9fZ3GZGVlac+ePQQsF1WYDla9evV+N/UfOXKkHKsBAKCUymlqbdiwYVq4cKE++ugjBQcHO9ZMhYaGyt/fXxaLRUlJSZo0aZJiYmIUExOjSZMmKSAgQAMHDnSMHTJkiEaOHKnq1asrLCxMo0aNUmxsrDp27Fgu1+GpKkzASkpKcvr5woUL2rlzp1avXq2nnnrKPUUBAHCNyuvLnufMmSNJio+Pd9o/b948DR48WJI0evRoFRQU6PHHH1dubq6aN2+uNWvWKDg42DE+LS1NPj4+6tevnwoKCtShQwfNnz9f3t7e5XIdnqrCPAframbNmqVt27ZViIXuPAcLlQHPwUKlUIbPwbqQ2M2l831fX2VSJXCnCr8Gq1u3blq6dKm7ywAAACixCjNFeDVLlixxPDQNAIAKr5ymCFGxVZiA1aRJE6dF7oZhKDs7W6dOndLs2bPdWBkAACXH86MgVaCAdc899zh9KL28vFSzZk3Fx8fr5ptvdmNl/8XaFFQGjwVGubsEoMy9ZpwpuxengwVVoICVkpLi7hIAAHAdHSyoAi1y9/b2Vk5OTrH9P/74I7eKAgCuHxaLaxs8QoUJWFd7WoTdbpefn185VwMAAFB6bp8ifPXVVyVdWhT4xhtvKCgoyHGsqKhImzZtqjBrsAAA+EN0oaAKELDS0tIkXepgvfbaa07TgX5+frrxxhv12muvuas8AACujVeFmRyCG7k9YGVmZkqS2rVrpw8//NDp27wBALju0MGCKkDAuuzzzz93dwkAALiOgAVVoEXuf/7znzV58uRi+1988UXdd999bqgIAIBS4C5CqAIFrI0bN6pHjx7F9nft2lWbNm1yQ0UAAAClU2GmCM+dO3fFxzH4+vrqzJkyfOIuAABmYpE7VIE6WI0bN9bixYuL7V+0aJEaNWrkhooAACgFpgihCtTBGjdunPr27avDhw+rffv2kqTPPvtMCxcu1JIlS9xcHQAAJURIgipQwOrVq5eWL1+uSZMmacmSJfL399ftt9+u9evXKyQkxN3lAQBQMgQsqAIFLEnq0aOHY6H7zz//rPfee09JSUn6+uuvVVRU5ObqAAAoAdZgQRVoDdZl69ev11/+8hdFRkZq5syZ6t69u7Zt2+busgAAAEqsQnSwjh8/rvnz5+utt95Sfn6++vXrpwsXLmjp0qUscAcAXF+YIoQqQAere/fuatSokfbt26cZM2boxIkTmjFjhrvLAgCgdLiLEKoAHaw1a9boiSee0NChQxUTE+PucgAAcA0hCaoAHax//etfOnv2rJo1a6bmzZtr5syZOnXqlLvLAgCgVCxeXi5t8Axu/38yLi5Oc+fOVVZWlhITE7Vo0SLVrl1bFy9e1Nq1a3X27Fl3lwgAQMkxRQhVgIB1WUBAgB5++GFt3rxZGRkZGjlypCZPnqxatWqpV69e7i4PAACgxCpMwPq1hg0baurUqTp+/Lj+8Y9/uLscAABKjg4WVAEWuf8eb29v9e7dW71793Z3KQAAlAwhCargAQsAgOsOC9UhAhYAAOaigwURsAAAMBcBC6qgi9wBAMAf27Rpk3r27KnIyEhZLBYtX77c6fjgwYNlsVicthYtWjiNsdvtGjFihGrUqKHAwED16tVLx48fL8er8EwELAAAzFSOdxHm5+fr9ttv18yZM686pmvXrsrKynJsK1eudDqelJSkZcuWadGiRdq8ebPOnTunhIQEFRUVlerycQlThAAAmKkcF7l369ZN3bp1+90xVqtVNpvtisfy8vL05ptvasGCBerYsaMk6d1331VUVJTWrVunLl26mF5zZUEHCwAAM7nYwbLb7Tpz5ozTZrfbS13Ohg0bVKtWLTVo0ECPPvqocnJyHMe2b9+uCxcuqHPnzo59kZGRaty4sdLT0136NVR2BCwAAMzkYsBKTU1VaGio05aamlqqUrp166b33ntP69ev18svv6ytW7eqffv2jsCWnZ0tPz8/VatWzem88PBwZWdnu/yrqMyYIgQAwEwuThGOGTNGycnJTvusVmupXqt///6OPzdu3FjNmjVT3bp1tWLFCvXp0+eq5xmGIQt3Q7qEgAUAQAVitVpLHaj+SEREhOrWrauDBw9Kkmw2mwoLC5Wbm+vUxcrJyVHLli3LpIbKgilCAADMVIG/i/DHH3/U999/r4iICElS06ZN5evrq7Vr1zrGZGVlac+ePQQsF9HBAgDATOU4tXbu3DkdOnTI8XNmZqZ27dqlsLAwhYWFKSUlRX379lVERISOHj2qsWPHqkaNGrr33nslSaGhoRoyZIhGjhyp6tWrKywsTKNGjVJsbKzjrkKUDgELAAAzlWPA2rZtm9q1a+f4+fLarUGDBmnOnDnKyMjQO++8o59//lkRERFq166dFi9erODgYMc5aWlp8vHxUb9+/VRQUKAOHTpo/vz58vb2Lrfr8EQWwzAMdxdx3fglz90VAGXuscAod5cAlLnXjDNl9tpFM0a6dL73iJdNqgTuxBosAAAAkzFFCACAmXi8AUTAAgDAXAQsiIAFAIC5LKy+AQELAABzedHBAgELAABz0cGCuIsQAADAdHSwAAAwE4vcIQIWAADm8mJyCAQsAADMRQcLImABAGAuFrlDBCwAAMxFBwviLkIAAADT0cECAMBMLHKHCFgAAJiLKUKIgAUAgLlY5A5VsjVYJ0+e1N///nd3lwEA8GReFtc2eIRKFbCys7P13HPPubsMAIAns3i5tsEjeNQU4e7du3/3+LfffltOlQAAgMrMowLWHXfcIYvFIsMwih27vN/C4kMAQFni3xnIwwJW9erVNWXKFHXo0OGKx/fu3auePXuWc1UAgEqFaT7IwwJW06ZNdeLECdWtW/eKx3/++ecrdrcAADANC9UhDwtYiYmJys/Pv+rxG264QfPmzSvHigAAlQ5ThJCHBax77733d49Xq1ZNgwYNKqdqAACVElOEUCV7TAMAAEB58KgOFgAAbscaLIiABQCAuZgihAhYAACYi0XuEAELAABz0cGCPHSR++rVq7V582bHz7NmzdIdd9yhgQMHKjc3142VAQA8Hl/2DHlowHrqqad05swZSVJGRoZGjhyp7t2768iRI0pOTnZzdQAAmGPTpk3q2bOnIiMjZbFYtHz5cqfjhmEoJSVFkZGR8vf3V3x8vPbu3es0xm63a8SIEapRo4YCAwPVq1cvHT9+vByvwjN5ZMDKzMxUo0aNJElLly5VQkKCJk2apNmzZ2vVqlVurg4A4NEsXq5t1yA/P1+33367Zs6cecXjU6dO1bRp0zRz5kxt3bpVNptNnTp10tmzZx1jkpKStGzZMi1atEibN2/WuXPnlJCQoKKiIpd+DZWdR67B8vPz0y+//CJJWrdunR566CFJUlhYmKOzBQBAmSjHRe7dunVTt27drnjMMAxNnz5dzzzzjPr06SNJevvttxUeHq6FCxcqMTFReXl5evPNN7VgwQJ17NhRkvTuu+8qKipK69atU5cuXcrtWjyNRwas1q1bKzk5Wa1atdJXX32lxYsXS5IOHDigOnXquLk6/JGt23fozXfe1Z593+jU6dOaNW2qOraLd3dZQIm1eWyI2gwdouo33iBJytr7jVb8fYr2rl4rSXrNuPJ/6C196lmtfelVSVLy5yvUIP5PTse3LlqqN+//axlWDlN4uTY5ZLfbZbfbnfZZrVZZrdZrep3MzExlZ2erc+fOTq/Ttm1bpaenKzExUdu3b9eFCxecxkRGRqpx48ZKT08nYLnAI6cIZ86cKR8fHy1ZskRz5sxR7dq1JUmrVq1S165d3Vwd/sgvBefVsEGMxv/tKXeXApRK7vEftPxvKUptFq/UZvH6dv1GDf3oH4podLMkabQt2ml7+69DdfHiRe1c+rHT6/zrf+c5jXsv8Ul3XA6ulcXi0paamqrQ0FCnLTU19ZrLyM7OliSFh4c77Q8PD3ccy87Olp+fn6pVq3bVMSgdj+xg3XDDDfrkk0+K7U9LS3NDNbhWbVu3VNvWLd1dBlBqGZ+sdvr5o2efV5uhj6hei7uUte8bnTmZ43T89nt66MDnm3Q686jT/sJfCoqNxXXAxcc0jBkzptgNWdfavXIq5zdTloZhFNv3WyUZg9/nkR2sHTt2KCMjw/HzRx99pN69e2vs2LEqLCx0Y2UAKhuLl5ea9e8rv8AAZf7fV8WOB9eqqdgeXfTFmwuKHbv7gX566VSmxu/5Un1fnChrUFB5lAw3s1qtCgkJcdpKE7BsNpskFetE5eTkOLpaNptNhYWFxR5h9OsxKB2PDFiJiYk6cOCAJOnIkSMaMGCAAgIC9MEHH2j06NFurg5AZRDZuJGmnz2hmfbTGvhaml6/9wFl7f+22Li4QQN1/uw57fzQeXrwq/fe15v3P6xp8d218vmpatK3lx778N3yKh+ucHGK0Cz16tWTzWbT2rVrHfsKCwu1ceNGtWx5aZagadOm8vX1dRqTlZWlPXv2OMagdDxyivDAgQO64447JEkffPCB2rRpo4ULF+qLL77QgAEDNH369D98jSsuMiyyu9SmBVB5nPz2oF64o7X8q4bqzr69NOjt1zStbbdiIavlww/qq/fe179/8/fN5jfedvz5xN79yjl4WGO3b1JUk9v1/c6vy+UaUEouLnK/FufOndOhQ4ccP2dmZmrXrl0KCwvTDTfcoKSkJE2aNEkxMTGKiYnRpEmTFBAQoIEDB0qSQkNDNWTIEI0cOVLVq1dXWFiYRo0apdjYWMddhSgdj+xgGYahixcvSrr0mIbu3btLkqKionT69OkSvcYVFxm+NK3MagbgWYouXNCpw0d0bPtOLR/7nI5/naF2Tw51GhPdOk62mxs4hamrObZjl/5dWKhaMTeVVckwSzl2sLZt26YmTZqoSZMmkqTk5GQ1adJE48ePlySNHj1aSUlJevzxx9WsWTP98MMPWrNmjYKDgx2vkZaWpt69e6tfv35q1aqVAgIC9M9//lPe3t7m/U4qIY/sYDVr1kwTJ05Ux44dtXHjRs2ZM0fSpWRf0jnlKy4yLDpveq0AKgeLxSLf33TAWw15SN9t26Efdu/5w/Mjb71FPn5+ysvizq4Krxy/izA+Pl6GYVy9FItFKSkpSklJueqYKlWqaMaMGZoxY0YZVFh5eWTAmj59uh544AEtX75czzzzjKKjoyVJS5YsKfGc8hWfOfLL1T/EME/+L7/o2Pf//ZqG4z+c0P5vDyg0JESRETY3VgaUzD0vjNfeVWuV+/0PsgYH6a4BfdUg/k+a0bWPY0yV4GDdeV9vLRn5TLHza9Svp7sf6Kc9K9co//SPimh0s/q+/IKO7dilw19sKc9LQWlw9x3koQHrtttuc7qL8LIXX3yRlud1YM++/Xro0f9OpaS+PF2SdG/PHpr89wluqgoouZDwWvrrgv9VSIRNBXln9MPuPZrRtY/2r/vcMabZgL6yWCza+o8lxc4vKizUzR3aqv2TQ2UNClTu9z9oz4pP9clzk2X8Z/kDgIrNYvxebxHOfslzdwVAmXssMMrdJQBl7mpP0zdD0YZFLp3vHT/ApErgTh7ZwSoqKlJaWpref/99HTt2rNizr3766Sc3VQYA8HheTBHCQ+8ifO655zRt2jT169dPeXl5Sk5OVp8+feTl5fW7C/0AAHCZxcu1DR7BI/+ffO+99zR37lyNGjVKPj4+uv/++/XGG29o/Pjx2rKFBaIAgDJUQR40CvfyyICVnZ2t2NhYSVJQUJDy8i6tnUpISNCKFSvcWRoAwNPRwYI8NGDVqVNHWVlZkqTo6GitWbNGkrR161aexA4AAMqcRwase++9V5999pkk6cknn9S4ceMUExOjhx56SA8//LCbqwMAeDKLxeLSBs/gkXcRTp482fHnP//5z6pTp47S09MVHR2tXr16ubEyAIDHY5oP8tCA9VstWrRQixYt3F0GAKAyIGBBHhSwPv744xKPpYsFACgzPAcL8qCA1bt37xKNs1gsKioqKttiAACVFx0syIMC1kW+nwsAAFQQHhOwAACoELgTEPKwxzSsX79ejRo10pkzxb/EMy8vT7feeqs2bdrkhsoAAJUGDxqFPCxgTZ8+XY8++qhCQkKKHQsNDVViYqLS0tLcUBkAoNLgq3IgDwtYX3/9tbp27XrV4507d9b27dvLsSIAQKVDBwvysDVYJ0+elK+v71WP+/j46NSpU+VYEQCg0uExDZCHdbBq166tjIyMqx7fvXu3IiIiyrEiAABQGXlUwOrevbvGjx+v8+fPFztWUFCgCRMmKCEhwQ2VAQAqDaYIIcliGIbh7iLMcvLkSd15553y9vbW8OHD1bBhQ1ksFu3fv1+zZs1SUVGRduzYofDw8NK9wS955hYMVECPBUa5uwSgzL1mFL/b3CwXMza4dL5XbLwZZcDNPGoNVnh4uNLT0zV06FCNGTNGl7OjxWJRly5dNHv27NKHKwAASoIuFORhAUuS6tatq5UrVyo3N1eHDh2SYRiKiYlRtWrV3F0aAKAy4FELkAcGrMuqVaumu+66y91lAAAqGzpYkIctcgcAAKgIPLaDBQCAW3jRuwABCwAAU1lYgwURsAAAMBdrsCACFgAA5qKDBbHIHQAAc5XTk9xTUlJksVicNpvN5jhuGIZSUlIUGRkpf39/xcfHa+/evWVxxbgCAhYAANepW2+9VVlZWY7t19/HO3XqVE2bNk0zZ87U1q1bZbPZ1KlTJ509e9aNFVceTBECAGCmcpwi9PHxcepaXWYYhqZPn65nnnlGffr0kSS9/fbbCg8P18KFC5WYmFhuNVZWdLAAADCTl5dr2zU4ePCgIiMjVa9ePQ0YMEBHjhyRJGVmZio7O1udO3d2jLVarWrbtq3S09NNvVxcGR0sAADM5GIHy263y263O+2zWq2yWq1O+5o3b6533nlHDRo00MmTJzVx4kS1bNlSe/fuVXZ2tiQV+/7d8PBwfffddy7Vh5KhgwUAgJlcXOSempqq0NBQpy01NbXY23Tr1k19+/ZVbGysOnbsqBUrVki6NBXoKOU3Yc8wDJ7TVU4IWAAAVCBjxoxRXl6e0zZmzJg/PC8wMFCxsbE6ePCgY13W5U7WZTk5OcW6WigbBCwAAMxksbi0Wa1WhYSEOG2/nR68Ervdrv379ysiIkL16tWTzWbT2rVrHccLCwu1ceNGtWzZsiyvHv/BGiwAAExVPlNwo0aNUs+ePXXDDTcoJydHEydO1JkzZzRo0CBZLBYlJSVp0qRJiomJUUxMjCZNmqSAgAANHDiwXOqr7AhYAACYqZzWOB0/flz333+/Tp8+rZo1a6pFixbasmWL6tatK0kaPXq0CgoK9Pjjjys3N1fNmzfXmjVrFBwcXC71VXYWwzAMdxdx3fglz90VAGXuscAod5cAlLnXjDNl9trG8f0unW+pc4tJlcCd6GABAGAq7tIDi9wBAABMRwcLAAAz8ZwpiIAFAIC5yFcQAQsAAJORsEDAAgDAXEwRQgQsAADMRcCCuIsQAADAdHSwAAAwFR0sELAAADAXU4QQAQsAAJMRsEDAAgDAXHSwIAIWAADmImBB3EUIAABgOjpYAACYig4WCFgAAJjKwhQhRMACAMBcBCyIgAUAgMkIWCBgAQBgLjpYEHcRAgAAmI4OFgAAZqKDBRGwAAAwGQELBCwAAMxFBwsiYAEAYC7yFUTAAgDAZCQscBchAACA6ehgAQBgJtZgQQQsAADMRcCCCFgAAJiMgAUCFgAA5qKDBRGwAAAwFwEL4i5CAAAA09HBAgDAVHSwQMACAMBcTBFCksUwDMPdRQBXYrfblZqaqjFjxshqtbq7HKBM8DkHPBMBCxXWmTNnFBoaqry8PIWEhLi7HKBM8DkHPBOL3AEAAExGwAIAADAZAQsAAMBkBCxUWFarVRMmTGDhLzwan3PAM7HIHQAAwGR0sAAAAExGwAIAADAZAQsAAMBkBCyUC4vFouXLl7u7DKBM8TkHcBkBCy7Lzs7WiBEjVL9+fVmtVkVFRalnz5767LPP3F2aJMkwDKWkpCgyMlL+/v6Kj4/X3r173V0WrjMV/XP+4YcfqkuXLqpRo4YsFot27drl7pKASo2ABZccPXpUTZs21fr16zV16lRlZGRo9erVateunYYNG+bu8iRJU6dO1bRp0zRz5kxt3bpVNptNnTp10tmzZ91dGq4T18PnPD8/X61atdLkyZPdXQoASTIAF3Tr1s2oXbu2ce7cuWLHcnNzHX+WZCxbtszx8+jRo42YmBjD39/fqFevnvHss88ahYWFjuO7du0y4uPjjaCgICM4ONi48847ja1btxqGYRhHjx41EhISjKpVqxoBAQFGo0aNjBUrVlyxvosXLxo2m82YPHmyY9/58+eN0NBQ47XXXnPx6lFZVPTP+a9lZmYakoydO3eW+noBuM7HzfkO17GffvpJq1ev1gsvvKDAwMBix6tWrXrVc4ODgzV//nxFRkYqIyNDjz76qIKDgzV69GhJ0gMPPKAmTZpozpw58vb21q5du+Tr6ytJGjZsmAoLC7Vp0yYFBgZq3759CgoKuuL7ZGZmKjs7W507d3bss1qtatu2rdLT05WYmOjCbwCVwfXwOQdQ8RCwUGqHDh2SYRi6+eabr/ncZ5991vHnG2+8USNHjtTixYsd//AcO3ZMTz31lOO1Y2JiHOOPHTumvn37KjY2VpJUv379q75Pdna2JCk8PNxpf3h4uL777rtrrhuVz/XwOQdQ8bAGC6Vm/OdLACwWyzWfu2TJErVu3Vo2m01BQUEaN26cjh075jienJysRx55RB07dtTkyZN1+PBhx7EnnnhCEydOVKtWrTRhwgTt3r37D9/vtzUahlGqulH5XE+fcwAVBwELpRYTEyOLxaL9+/df03lbtmzRgAED1K1bN33yySfauXOnnnnmGRUWFjrGpKSkaO/everRo4fWr1+vRo0aadmyZZKkRx55REeOHNGDDz6ojIwMNWvWTDNmzLjie9lsNkn/7WRdlpOTU6yrBVzJ9fA5B1ABuXUFGK57Xbt2vebFvy+99JJRv359p7FDhgwxQkNDr/o+AwYMMHr27HnFY3/729+M2NjYKx67vMh9ypQpjn12u51F7rgmFf1z/msscgcqBjpYcMns2bNVVFSku+++W0uXLtXBgwe1f/9+vfrqq4qLi7viOdHR0Tp27JgWLVqkw4cP69VXX3X8V7skFRQUaPjw4dqwYYO+++47ffHFF9q6datuueUWSVJSUpI+/fRTZWZmaseOHVq/fr3j2G9ZLBYlJSVp0qRJWrZsmfbs2aPBgwcrICBAAwcONP8XAo9U0T/n0qXF+Lt27dK+ffskSd9++6127dpVrHsLoJy4O+Hh+nfixAlj2LBhRt26dQ0/Pz+jdu3aRq9evYzPP//cMUa/uX39qaeeMqpXr24EBQUZ/fv3N9LS0hz/ZW+3240BAwYYUVFRhp+fnxEZGWkMHz7cKCgoMAzDMIYPH27cdNNNhtVqNWrWrGk8+OCDxunTp69a38WLF40JEyYYNpvNsFqtRps2bYyMjIyy+FXAg1X0z/m8efMMScW2CRMmlMFvA8AfsRjGf1ZwAgAAwBRMEQIAAJiMgAUAAGAyAhYAAIDJCFgAAAAmI2ABAACYjIAFAABgMgIWAACAyQhYQCWWkpKiO+64w/Hz4MGD1bt373Kv4+jRo7JYLNq1a1e5vzcAlAUCFlABDR48WBaLRRaLRb6+vqpfv75GjRql/Pz8Mn3fV155RfPnzy/RWEIRAFydj7sLAHBlXbt21bx583ThwgX961//0iOPPKL8/HzNmTPHadyFCxfk6+trynuGhoaa8joAUNnRwQIqKKvVKpvNpqioKA0cOFAPPPCAli9f7pjWe+utt1S/fn1ZrVYZhqG8vDz9v//3/1SrVi2FhISoffv2+vrrr51ec/LkyQoPD1dwcLCGDBmi8+fPOx3/7RThxYsXNWXKFEVHR8tqteqGG27QCy+8IEmqV6+eJKlJkyayWCyKj493nDdv3jzdcsstqlKlim6++WbNnj3b6X2++uorNWnSRFWqVFGzZs20c+dOE39zAOB+dLCA64S/v78uXLggSTp06JDef/99LV26VN7e3pKkHj16KCwsTCtXrlRoaKhef/11dejQQQcOHFBYWJjef/99TZgwQbNmzdKf/vQnLViwQK+++qrq169/1fccM2aM5s6dq7S0NLVu3VpZWVn65ptvJF0KSXfffbfWrVunW2+9VX5+fpKkuXPnasKECZo5c6aaNGminTt36tFHH1VgYKAGDRqk/Px8JSQkqH379nr33XeVmZmpJ598sox/ewBQztz8ZdMArmDQoEHGPffc4/j5yy+/NKpXr27069fPmDBhguHr62vk5OQ4jn/22WdGSEiIcf78eafXuemmm4zXX3/dMAzDiIuLMx577DGn482bNzduv/32K77vmTNnDKvVasydO/eKNWZmZhqSjJ07dzrtj4qKMhYuXOi07/nnnzfi4uIMwzCM119/3QgLCzPy8/Mdx+fMmXPF1wKA6xVThEAF9cknnygoKEhVqlRRXFyc2rRpoxkzZkiS6tatq5o1azrGbt++XefOnVP16tUVFBTk2DIzM3X48GFJ0v79+xUXF+f0Hr/9+df2798vu92uDh06lLjmU6dO6fvvv9eQIUOc6pg4caJTHbfffrsCAgJKVAcAXI+YIgQqqHbt2mnOnDny9fVVZGSk00L2wMBAp7EXL15URESENmzYUOx1qlatWqr39/f3v+ZzLl68KOnSNGHz5s2djl2eyjQMo1T1AMD1hIAFVFCBgYGKjo4u0dg777xT2dnZ8vHx0Y033njFMbfccou2bNmihx56yLFvy5YtV33NmJgY+fv767PPPtMjjzxS7PjlNVdFRUWOfeHh4apdu7aOHDmiBx544Iqv26hRIy1YsEAFBQWOEPd7dQDA9YgpQsADdOzYUXFxcerdu7c+/fRTHT16VOnp6Xr22We1bds2SdKTTz6pt956S2+99ZYOHDigCRMmaO/evVd9zSpVqujpp5/W6NGj9c477+jw4cPasmWL3nzzTUlSrVq15O/vr9WrV+vkyZPKy8uTdOnhpampqXrllVd04MABZWRkaN68eZo2bZokaeDAgfLy8tKQIUO0b98+rVy5Ui+99FIZ/4YAoHwRsAAPYLFYtHLlSrVp00YPP/ywGjRooAEDBujo0aMKDw+XJPXv31/jx4/X008/raZNm+q7777T0KFDf/d1x40bp5EjR2r8+PG65ZZb1L9/f+Xk5EiSfHx89Oqrr+r1119XZGSk7rnnHknSI488ojfeeEPz589XbGys2rZtq/nz5zse6xAUFKR//vOf2rdvn5o0aaJnnnlGU6ZMKcPfDgCUP4vBgggAAABT0cECAAAwGQELAADAZAQsAAAAk/1/kmr+ZkjS9U4AAAAASUVORK5CYII=" alt="Confusion Matrix"> | |
| </div> | |
| </div> | |
| </div> | |
| <div class="container"> | |
| <div class="header">MODEL: FEEDFORWARD_k3</div> | |
| <div style="display: flex;"> | |
| <div class="section"> | |
| <h2 class='mod_sum'>Model Architecture</h2> | |
| <pre>Model: "FEEDFORWARD_k3" | |
| ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓ | |
| ┃ Layer (type) ┃ Output Shape ┃ Param # ┃ | |
| ┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩ | |
| │ dense_5 (Dense) │ (None, 256) │ 2,209,792 │ | |
| ├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤ | |
| │ dropout_4 (Dropout) │ (None, 256) │ 0 │ | |
| ├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤ | |
| │ dense_6 (Dense) │ (None, 128) │ 32,896 │ | |
| ├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤ | |
| │ dropout_5 (Dropout) │ (None, 128) │ 0 │ | |
| ├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤ | |
| │ dense_7 (Dense) │ (None, 64) │ 8,256 │ | |
| ├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤ | |
| │ dropout_6 (Dropout) │ (None, 64) │ 0 │ | |
| ├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤ | |
| │ dense_8 (Dense) │ (None, 32) │ 2,080 │ | |
| ├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤ | |
| │ dropout_7 (Dropout) │ (None, 32) │ 0 │ | |
| ├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤ | |
| │ dense_9 (Dense) │ (None, 1) │ 33 │ | |
| └──────────────────────────────────────┴─────────────────────────────┴─────────────────┘ | |
| Total params: 6,759,173 (25.78 MB) | |
| Trainable params: 2,253,057 (8.59 MB) | |
| Non-trainable params: 0 (0.00 B) | |
| Optimizer params: 4,506,116 (17.19 MB) | |
| </pre> | |
| </div> | |
| <div class="section learning-curve"> | |
| <h2>Learning Curve</h2> | |
| <img src="data:image/png;base64,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" alt="Learning Curve"> | |
| </div> | |
| </div> | |
| <div style="display: flex;"> | |
| <div class="section class_dist"> | |
| <h2>Class Distribution</h2> | |
| <pre> Count Percentage | |
| class | |
| 1 1876 50.35 | |
| 0 1850 49.65</pre> | |
| <h3>Additional Metrics</h3> | |
| <ul> | |
| <li>Total Samples: 3726</li> | |
| <li>Imbalance Ratio: 1.01</li> | |
| </ul> | |
| </div> | |
| <div class="section"> | |
| <h2>Classification Report</h2> | |
| <pre> precision recall f1-score support | |
| Class 0 0.9946 1.0000 0.9973 370 | |
| Class 1 1.0000 0.9947 0.9973 376 | |
| accuracy 0.9973 746 | |
| macro avg 0.9973 0.9973 0.9973 746 | |
| weighted avg 0.9973 0.9973 0.9973 746 | |
| </pre> | |
| <h3>Metrics</h3> | |
| <div class="metrics"> | |
| <ul> | |
| <li>True Positives (TP): 374</li> | |
| <li>True Negatives (TN): 370</li> | |
| </ul> | |
| <ul> | |
| <li>False Positives (FP): 0</li> | |
| <li>False Negatives (FN): 2</li> | |
| </ul> | |
| </div> | |
| </div> | |
| <div class="section confusion-matrix"> | |
| <h2>Confusion Matrix</h2> | |
| <img src="data:image/png;base64,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" alt="Confusion Matrix"> | |
| </div> | |
| </div> | |
| </div> | |
| <div class="container"> | |
| <div class="header">MODEL: FEEDFORWARD_k4</div> | |
| <div style="display: flex;"> | |
| <div class="section"> | |
| <h2 class='mod_sum'>Model Architecture</h2> | |
| <pre>Model: "FEEDFORWARD_k4" | |
| ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓ | |
| ┃ Layer (type) ┃ Output Shape ┃ Param # ┃ | |
| ┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩ | |
| │ dense_10 (Dense) │ (None, 256) │ 34,301,952 │ | |
| ├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤ | |
| │ dropout_8 (Dropout) │ (None, 256) │ 0 │ | |
| ├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤ | |
| │ dense_11 (Dense) │ (None, 128) │ 32,896 │ | |
| ├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤ | |
| │ dropout_9 (Dropout) │ (None, 128) │ 0 │ | |
| ├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤ | |
| │ dense_12 (Dense) │ (None, 64) │ 8,256 │ | |
| ├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤ | |
| │ dropout_10 (Dropout) │ (None, 64) │ 0 │ | |
| ├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤ | |
| │ dense_13 (Dense) │ (None, 1) │ 65 │ | |
| └──────────────────────────────────────┴─────────────────────────────┴─────────────────┘ | |
| Total params: 103,029,509 (393.03 MB) | |
| Trainable params: 34,343,169 (131.01 MB) | |
| Non-trainable params: 0 (0.00 B) | |
| Optimizer params: 68,686,340 (262.02 MB) | |
| </pre> | |
| </div> | |
| <div class="section learning-curve"> | |
| <h2>Learning Curve</h2> | |
| <img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAoAAAAHgCAYAAAA10dzkAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8fJSN1AAAACXBIWXMAAA9hAAAPYQGoP6dpAABOPUlEQVR4nO3dfZzNdf7/8eeZM9djZlwMc8FghI0xJFQIub6oiSiSwkalS8OWi1qhbzVpN9myxBZtu5SEVqUklcv6JRnJKJIMmYkRc4W5OOfz+2PM4ZjBYGY+M+fzuO+e25nP+/P+fD6v95xPznM+F+fYDMMwBAAAAMvwMrsAAAAAVCwCIAAAgMUQAAEAACyGAAgAAGAxBEAAAACLIQACAABYDAEQAADAYgiAAAAAFkMABAAAsBgCIAAAgMUQAAEAACyGAAgAAGAxBEAAAACLIQACAABYDAEQAADAYgiAAAAAFkMABAAAsBgCIAAAgMUQAAEAACyGAAgAAGAxBEAAAACLIQACAABYDAEQAADAYgiAAAAAFkMABAAAsBgCIAAAgMUQAAEAACyGAAgAAGAxBEAAAACLIQACAABYDAEQAADAYgiAAAAAFkMABAAAsBgCIAAAgMUQAAEAACyGAAgAAGAxBEAAAACLIQACAABYDAEQAADAYgiAAAAAFkMABAAAsBgCIAAAgMUQAAEAACyGAAgAAGAxBEAAAACLIQACAABYDAEQAADAYgiAAAAAFkMABAAAsBgCIAAAgMUQAAEAACyGAAgAAGAxBEAAAACLIQACAABYDAEQAADAYgiAAAAAFuNtdgFVmdPp1KFDhxQcHCybzWZ2OQAAoBQMw1BWVpaioqLk5WXNY2EEwCtw6NAhRUdHm10GAAC4DAcOHFC9evXMLsMUBMArEBwcLKlwBwoJCTG5GgAAUBqZmZmKjo52vY9bEQHwChSd9g0JCSEAAgBQxVj58i1rnvgGAACwMAIgAACAxRAAAQAALIYACAAAYDEEQAAAAIshAAIAAFgMARAAAMBiCIAAAAAWQwAEAACwGI8JgOvXr1d8fLyioqJks9n0/vvvX3SZdevWqU2bNvL391ejRo302muvlX+hAAAAJvOYAJiTk6NWrVpp9uzZpeq/b98+9evXT506ddK2bdv05JNP6rHHHtOyZcvKuVJURWk5afom9Rul5aSZXcoVYRyVC+OoXBhH5eIp46isPOa7gPv27au+ffuWuv9rr72m+vXra9asWZKkZs2a6dtvv9Xf//53DRo0qJyqLL1Dv+xQ6o/fKfLqaxXVKM7sci6bJ4xj+Z7lenX1NIX/4dDvNe16tPc0DWwy0OyyLhnjqFyW71mu6V9Nl9Nwysvmpantp1bZcXjK6+Ep4/CU/coTxlGZ2QzDMMwuoqzZbDatWLFCAwYMOG+fzp07q3Xr1vrHP/7haluxYoUGDx6sEydOyMfHp9gyubm5ys3NdU1nZmYqOjpaGRkZCgkJKbP6P7yvn2I27JOXJKekfe0i5d0yVs7TL5UhZ+GzYcgwJENF7YYKX87ClrOnXf1PPxetx3268H8yzl1ep5d3utoL/+88s2Wj+PZD9qSpZVKmaxzft6qmPxrXOVOf4b491xqNs0bgqu2c+oyzpl1jODPt9rsy5L69s8Z29vTZ23Utbxi66jeHOiYbrnFsam7Tz3VtkqrSl4gbavyb4ZHj+DLOph0xXnJ42+TwkgrsZx7u07YS2qQCL8nwqtjfQdG+VzPTUOQxQ6k1bPojxCabbBX65fQ2w5C3Q/J2SHaH5O3UOdNn5ns7JPtZ870dhuwOKfZXpzr/4Hn71bo4m35o6KUC75L3mzPT59mv7JLTJqkCX8/Ksl9dqZLGcTzUrtWDVisiKKJMtpGZmanQ0NAyf/+uSjzmCOClSktLU3h4uFtbeHi4CgoKlJ6ersjIyGLLJCYmavr06eVa16FfdqjRhn2ufzq9JF21JVXaklqu2y1vXpKu2Z4tbc82u5Qr4iWpU7KhTslV++8mTxpHtx2Guu1wXNF6nDb3QHjuzw639osFzbOXtZXcx0u6+oChHklnAsfnrWzaXc9WGLzOCWPeDsM1fW5QKzGYnTPfrf9Z67GX8cvvSftV1x2Gul7hfiVJ+We95o4L7GPnC5IXC57nrutPB933q0/a2PR9TNUJf0Va7jPUZ+uZcczrZ+hArwNlFgBh4QAoqdhfREVHm873l9LkyZM1fvx413TREcCylPrjdwos0zUCuBgvQ/ItKHxc3KWEm9L19ZLUY7uhHturdnBCcT6OwsfFXeprf/H+XpL6bTXUb2vV3q+8JN3/sVM1H/E3uxSPYtkAGBERobQ09wtLDx8+LG9vb9WqVavEZfz8/OTn51eudUVefa2Oyf3uHKdNSh3dV/41a8tLNhX+3+v0mYXTh/cl2WyFS9lsp6ddfU7/XKxPYT/ZzpwisKmEddrOtNhOb9/LZnPrp6LlT68j88ghOV9+vdg4fMePUfXa9WSzeZ213OkKz1pnZeE4flxpzz8n21n/fho2myKefFL26tVNq+tSefo4aj/8sLwCAmTk58soKCh8dj3yZBQUSG5t5/Qptky+jIJ8Kc+9rSqx+fjI5uMjnX52Pby93afPbvM9vYxbH98Slimcdp48qcOzZnnufvXoo2f2q/y8wn2g2L5ykX2pIL9w38s7fx85neYNvoqwG1LokZNSI7Mr8RyWDYDt27fXBx984Nb26aefqm3btiVe/1dRohrFadejtyl89grZDclhk35/5Db1ePh502q6HHUlrS04Wmwc3e8ba3Zpl8wrwF+pT08t/Efay0tRz0xX9dtvN7usS8Y4roxhGJLDUfKbeF7hG72Rn+8eNM8TFgqOHlX6q69KZ1+CbbOpdkKCvMPCXEHs3OBVGMx8iwWxc8OcvL0r7Jov71q12K+ukOFwFA+Fxf4guVjwPL1f/eOVYvtVzXv/LHtwcIWMpSw4srL0x4KF7uPw8pJvg/rmFeWBPOYmkOzsbP3888+SpNatW2vmzJnq2rWratasqfr162vy5Mn67bff9NZbb0kq/BiYFi1a6IEHHtB9992nr776SmPGjNHbb79d6ruAy/Mi0kO/7FDaT9sU8afWVfbuWclzxpGflqa8/SnybVBfPhFV9xoUxlF5HH/vPbfAEVlFg5PkGa+H5Bnj8JT9qrzHwU0gHhQAv/zyS3Xt2rVY+4gRI/Tmm29q5MiR+vXXX/Xll1+65q1bt07jxo3Tzp07FRUVpYkTJ2rMmDGl3iY7EIAr4QmBA5WPp+xX5TkO3r89KACagR0IAICqh/dvD/omEAAAAJQOARAAAMBiCIAAAAAWQwAEAACwGAIgAACAxRAAAQAALIYACAAAYDEEQAAAAIshAAIAAFgMARAAAMBiCIAAAAAWQwAEAACwGAIgAACAxRAAAQAALIYACAAAYDEEQAAAAIshAAIAAFgMARAAAMBiCIAAAAAWQwAEAACwGAIgAACAxRAAAQAALIYACAAAYDEEQAAAAIshAAIAAFgMARAAAMBiCIAAAAAWQwAEAACwGAIgAACAxRAAAQAALIYACAAAYDEEQAAAAIshAAIAAFgMARAAAMBiCIAAAAAWQwAEAACwGAIgAACAxRAAAQAALIYACAAAYDEEQAAAAIshAAIAAFgMARAAAMBiCIAAAAAWQwAEAACwGAIgAACAxRAAAQAALIYACAAAYDEEQAAAAIshAAIAAFgMARAAAMBiCIAAAAAWQwAEAACwGAIgAACAxRAAAQAALIYACAAAYDEEQAAAAIvxqAA4Z84cxcTEyN/fX23atNGGDRsu2H/RokVq1aqVAgMDFRkZqT//+c86evRoBVULAABgDo8JgEuWLFFCQoKeeuopbdu2TZ06dVLfvn2VkpJSYv+NGzdq+PDhGjVqlHbu3KmlS5dqy5YtGj16dAVXDgAAULE8JgDOnDlTo0aN0ujRo9WsWTPNmjVL0dHRmjt3bon9v/76azVs2FCPPfaYYmJidOONN+qBBx7Qt99+W8GVAwAAVCyPCIB5eXnaunWrevXq5dbeq1cvbd68ucRlOnTooIMHD2rVqlUyDEO///673nvvPd18880VUTIAAIBpPCIApqeny+FwKDw83K09PDxcaWlpJS7ToUMHLVq0SEOGDJGvr68iIiJUvXp1vfrqq+fdTm5urjIzM90eAAAAVY1HBMAiNpvNbdowjGJtRZKTk/XYY4/p6aef1tatW/XJJ59o3759GjNmzHnXn5iYqNDQUNcjOjq6TOsHAACoCDbDMAyzi7hSeXl5CgwM1NKlS3Xbbbe52seOHaukpCStW7eu2DL33HOPTp06paVLl7raNm7cqE6dOunQoUOKjIwstkxubq5yc3Nd05mZmYqOjlZGRoZCQkLKeFQAAKA8ZGZmKjQ01NLv3x5xBNDX11dt2rTRmjVr3NrXrFmjDh06lLjMiRMn5OXlPny73S6p8MhhSfz8/BQSEuL2AAAAqGo8IgBK0vjx4/X6669rwYIF2rVrl8aNG6eUlBTXKd3Jkydr+PDhrv7x8fFavny55s6dq19++UWbNm3SY489puuuu05RUVFmDQMAAKDceZtdQFkZMmSIjh49qmeeeUapqalq0aKFVq1apQYNGkiSUlNT3T4TcOTIkcrKytLs2bP1l7/8RdWrV1e3bt00Y8YMs4YAAABQITziGkCzcA0BAABVD+/fHnQKGAAAAKVDAAQAALAYAiAAAIDFEAABAAAshgAIAABgMQRAAAAAiyEAAgAAWAwBEAAAwGIIgAAAABZDAAQAALAYAiAAAIDFEAABAAAshgAIAABgMQRAAAAAiyEAAgAAWAwBEAAAwGIIgAAAABZDAAQAALAYAiAAAIDFEAABAAAshgAIAABgMQRAAAAAiyEAAgAAWAwBEAAAwGIIgAAAABZDAAQAALAYAiAAAIDFEAABAAAshgAIAABgMQRAAAAAiyEAAgAAWAwBEAAAwGIIgAAAABZDAAQAALAYAiAAAIDFEAABAAAshgAIAABgMQRAAAAAiyEAAgAAWAwBEAAAwGIIgAAAABZDAAQAALAYAiAAAIDFEAABAAAshgAIAABgMQRAAAAAiyEAAgAAWAwBEAAAwGIIgAAAABbjbXYBAABcCofDofz8fLPLQCXm4+Mju91udhmVGgEQAFAlGIahtLQ0HT9+3OxSUAVUr15dERERstlsZpdSKREAAQBVQlH4q1OnjgIDA3ljR4kMw9CJEyd0+PBhSVJkZKTJFVVOBEAAQKXncDhc4a9WrVpml4NKLiAgQJJ0+PBh1alTh9PBJeAmEABApVd0zV9gYKDJlaCqKNpXuF60ZARAAECVwWlflBb7yoURAAEAACzGowLgnDlzFBMTI39/f7Vp00YbNmy4YP/c3Fw99dRTatCggfz8/HTVVVdpwYIFFVQtAMAKbrrpJiUkJJhdBuDGY24CWbJkiRISEjRnzhx17NhR8+bNU9++fZWcnKz69euXuMzgwYP1+++/64033lDjxo11+PBhFRQUVHDlAAAAFctjAuDMmTM1atQojR49WpI0a9YsrV69WnPnzlViYmKx/p988onWrVunX375RTVr1pQkNWzYsCJLBgAAMIVHnALOy8vT1q1b1atXL7f2Xr16afPmzSUus3LlSrVt21Yvvvii6tatq6ZNm+rxxx/XyZMnK6JkAICJUjNOavPedKVmVOy/+ceOHdPw4cNVo0YNBQYGqm/fvtqzZ49r/v79+xUfH68aNWooKChIsbGxWrVqlWvZYcOGqXbt2goICFCTJk20cOHCCq0fnsMjjgCmp6fL4XAoPDzcrT08PFxpaWklLvPLL79o48aN8vf314oVK5Senq6HHnpIf/zxx3mvA8zNzVVubq5rOjMzs+wGAQCoEEu2pGjy8h1yGpKXTUocGKch7Uq+VKisjRw5Unv27NHKlSsVEhKiiRMnql+/fkpOTpaPj48efvhh5eXlaf369QoKClJycrKqVasmSZoyZYqSk5P18ccfKywsTD///DMHLXDZPCIAFjn3lm/DMM57G7jT6ZTNZtOiRYsUGhoqqfA08u23365//vOfrg+RPFtiYqKmT59e9oUDAC5L/KsbdSQr9+IdT3M4DR3JPtPfaUgTl+3Q31fvlt2r9B8bUjvYTx88euMl1VoU/DZt2qQOHTpIkhYtWqTo6Gi9//77uuOOO5SSkqJBgwYpLi5OktSoUSPX8ikpKWrdurXatm0ricuWcGU8IgCGhYXJbrcXO9p3+PDhYkcFi0RGRqpu3bqu8CdJzZo1k2EYOnjwoJo0aVJsmcmTJ2v8+PGu6czMTEVHR5fRKAAAl+pIVq7SMk9d+XqySx8iL9euXbvk7e2t66+/3tVWq1Yt/elPf9KuXbskSY899pgefPBBffrpp+rRo4cGDRqkli1bSpIefPBBDRo0SN9995169eqlAQMGuIIkcKk84hpAX19ftWnTRmvWrHFrX7NmzXn/4+jYsaMOHTqk7OxsV9vu3bvl5eWlevXqlbiMn5+fQkJC3B4AAPPUDvZTRIh/qR+1q/mVvJ5ql7ie4JLXcyGGYZy3vehs1ejRo/XLL7/onnvu0Y4dO9S2bVu9+uqrkqS+fftq//79SkhI0KFDh9S9e3c9/vjjl1wHIEkyPMQ777xj+Pj4GG+88YaRnJxsJCQkGEFBQcavv/5qGIZhTJo0ybjnnntc/bOysox69eoZt99+u7Fz505j3bp1RpMmTYzRo0eXepsZGRmGJCMjI6PMxwMAOOPkyZNGcnKycfLkySte1zvf7DcaTfrIaDDxQ6PRpI+Md77ZXwYVnl+XLl2MsWPHGrt37zYkGZs2bXLNS09PNwICAoylS5eWuOykSZOMuLi4Eue99tprRnBwcLnU7AkutM/w/m0YHnEKWJKGDBmio0eP6plnnlFqaqpatGihVatWqUGDBpKk1NRUpaSkuPpXq1ZNa9as0aOPPqq2bduqVq1aGjx4sJ599lmzhgAAqABD2tVX56a19Wv6CTUMC1RkaPFrvstDkyZN1L9/f913332aN2+egoODNWnSJNWtW1f9+/eXJCUkJKhv375q2rSpjh07ps8//1zNmjWTJD399NNq06aNYmNjlZubqw8//NA1D7hUHhMAJemhhx7SQw89VOK8N998s1jb1VdfXey0MQDA80WGBlRY8DvbwoULNXbsWN1yyy3Ky8tT586dtWrVKvn4+EiSHA6HHn74YR08eFAhISHq06ePXn75ZUmFlztNnjxZv/76qwICAtSpUye98847FT4GeAabYZznogRcVGZmpkJDQ5WRkcH1gABQjk6dOqV9+/a5vu4TuJgL7TO8f3vITSAAAAAoPQIgAACAxRAAAQAALIYACAAAYDEEQAAAAIshAAIAAFgMARAAAMBiCIAAAAAWQwAEAACwGNMDYEFBgT777DPNmzdPWVlZkqRDhw4pOzvb5MoAADBfw4YNNWvWrFL1tdlsev/998u1HngGU78LeP/+/erTp49SUlKUm5urnj17Kjg4WC+++KJOnTql1157zczyAAAAPJKpRwDHjh2rtm3b6tixYwoIOPOl3LfddpvWrl1rYmUAAACey9QAuHHjRv31r3+Vr6+vW3uDBg3022+/mVQVAMDjZfwm7Vtf+FyO5s2bp7p168rpdLq133rrrRoxYoT27t2r/v37Kzw8XNWqVVO7du302Wefldn2d+zYoW7duikgIEC1atXS/fff73aJ1ZdffqnrrrtOQUFBql69ujp27Kj9+/dLkrZv366uXbsqODhYISEhatOmjb799tsyqw3mMjUAOp1OORyOYu0HDx5UcHCwCRUBADzed29Js1pI/44vfP7urXLb1B133KH09HR98cUXrrZjx45p9erVGjZsmLKzs9WvXz999tln2rZtm3r37q34+HilpKRc8bZPnDihPn36qEaNGtqyZYuWLl2qzz77TI888oikwmvwBwwYoC5duuj777/XV199pfvvv182m02SNGzYMNWrV09btmzR1q1bNWnSJPn4+FxxXagcTL0GsGfPnpo1a5bmz58vqfDi1ezsbE2dOlX9+vUzszQAQFUwr4uUfbj0/Z0OKef3M9OGU1r5qLT2WcnLXvr1VKsjPbDuot1q1qypPn36aPHixerevbskaenSpapZs6a6d+8uu92uVq1aufo/++yzWrFihVauXOkKapdr0aJFOnnypN566y0FBQVJkmbPnq34+HjNmDFDPj4+ysjI0C233KKrrrpKktSsWTPX8ikpKXriiSd09dVXS5KaNGlyRfWgcjE1AL788svq2rWrmjdvrlOnTumuu+7Snj17FBYWprffftvM0gAAVUH2YSnr0JWv5+xQWMaGDRum+++/X3PmzJGfn58WLVqkO++8U3a7XTk5OZo+fbo+/PBDHTp0SAUFBTp58mSZHAHctWuXWrVq5Qp/ktSxY0c5nU799NNP6ty5s0aOHKnevXurZ8+e6tGjhwYPHqzIyEhJ0vjx4zV69Gj95z//UY8ePXTHHXe4giKqPlNPAUdFRSkpKUmPP/64HnjgAbVu3VovvPCCtm3bpjp16phZGgCgKqhWRwqOKv0jKLzk9QSFX9p6qpX+PSo+Pl5Op1MfffSRDhw4oA0bNujuu++WJD3xxBNatmyZnnvuOW3YsEFJSUmKi4tTXl7eFf9qDMNwnc49V1H7woUL9dVXX6lDhw5asmSJmjZtqq+//lqSNG3aNO3cuVM333yzPv/8czVv3lwrVqy44rpQOZh6BFCSAgICdO+99+ree+81uxQAQFVTitOwxXz3lvRBgmQ4JJtdip8lXTu8rCtzCQgI0MCBA7Vo0SL9/PPPatq0qdq0aSNJ2rBhg0aOHKnbbrtNkpSdna1ff/21TLbbvHlz/fvf/1ZOTo7rKOCmTZvk5eWlpk2buvq1bt1arVu31uTJk9W+fXstXrxYN9xwgySpadOmatq0qcaNG6ehQ4dq4cKFrlpRtZkaAN9668IX3g4fXn7/QQIALOra4dJV3aU/fpFqNpJC65b7JocNG6b4+Hjt3LnTdfRPkho3bqzly5crPj5eNptNU6ZMKXbH8JVsc+rUqRoxYoSmTZumI0eO6NFHH9U999yj8PBw7du3T/Pnz9ett96qqKgo/fTTT9q9e7eGDx+ukydP6oknntDtt9+umJgYHTx4UFu2bNGgQYPKpDaYz9QAOHbsWLfp/Px8nThxQr6+vgoMDCQAAgDKR2jdCgl+Rbp166aaNWvqp59+0l133eVqf/nll3XvvfeqQ4cOCgsL08SJE5WZmVkm2wwMDNTq1as1duxYtWvXToGBgRo0aJBmzpzpmv/jjz/q3//+t44eParIyEg98sgjeuCBB1RQUKCjR49q+PDh+v333xUWFqaBAwdq+vTpZVIbzGczDMMwu4iz7dmzRw8++KCeeOIJ9e7d2+xyLigzM1OhoaHKyMhQSEiI2eUAgMc6deqU9u3bp5iYGPn7+5tdDqqAC+0zvH9Xgu8CPleTJk30wgsvFDs6CAAAgLJR6QKgJNntdh06VAa39QMA4CEWLVqkatWqlfiIjY01uzxUMaZeA7hy5Uq3acMwlJqaqtmzZ6tjx44mVQUAQOVz66236vrrry9xHt/QgUtlagAcMGCA27TNZlPt2rXVrVs3vfTSS+YUBQBAJRQcHMzXpKLMmBoAy+pWdwAAAJRepbwGEAAAAOWnwo8Ajh8/vtR9iz6rCAAAAGWnwgPgtm3bStXvfN9fCAAAgCtT4QHwiy++qOhNAgAA4CxcAwgAAGAxpt4FLElbtmzR0qVLlZKSory8PLd5y5cvN6kqAAAAz2XqEcB33nlHHTt2VHJyslasWKH8/HwlJyfr888/V2hoqJmlAQDgsfLz880uASYzNQA+//zzevnll/Xhhx/K19dX//jHP7Rr1y4NHjxY9evXN7M0AIAHS8tJ0zep3ygtJ61CtvfJJ5/oxhtvVPXq1VWrVi3dcsst2rt3r2v+wYMHdeedd6pmzZoKCgpS27Zt9f/+3/9zzV+5cqXatm0rf39/hYWFaeDAga55NptN77//vtv2qlevrjfffFOS9Ouvv8pms+ndd9/VTTfdJH9/f/33v//V0aNHNXToUNWrV0+BgYGKi4vT22+/7bYep9OpGTNmqHHjxvLz81P9+vX13HPPSZK6deumRx55xK3/0aNH5efnp88//7wsfm0oR6YGwL179+rmm2+WJPn5+SknJ0c2m03jxo3T/PnzzSwNAOChlu9Zrt7LemvUp6PUe1lvLd9T/pcb5eTkaPz48dqyZYvWrl0rLy8v3XbbbXI6ncrOzlaXLl106NAhrVy5Utu3b9eECRNcX5bw0UcfaeDAgbr55pu1bds2rV27Vm3btr3kGiZOnKjHHntMu3btUu/evXXq1Cm1adNGH374oX744Qfdf//9uueee9yC5+TJkzVjxgxNmTJFycnJWrx4scLDwyVJo0eP1uLFi5Wbm+vqv2jRIkVFRalr165X+BtDeTP1GsCaNWsqKytLklS3bl398MMPiouL0/Hjx3XixAkzSwMAVAFDPhyi9JPppe7vcDp09NRR17TTcGrq5ql65btXZPeyl3o9YQFhWnLLklL3HzRokNv0G2+8oTp16ig5OVmbN2/WkSNHtGXLFtWsWVOS1LhxY1ff5557TnfeeaemT5/uamvVqlWpt10kISHB7cihJD3++OOunx999FF98sknWrp0qa6//nplZWXpH//4h2bPnq0RI0ZIkq666irdeOONrjE9+uij+t///qfBgwdLkhYuXKiRI0fyUW5VgCkBMCkpSddcc406deqkNWvWKC4uToMHD9bYsWP1+eefa82aNerevbsZpQEAqpD0k+k6fOLwFa/n7FBYHvbu3aspU6bo66+/Vnp6uuvoXkpKipKSktS6dWtX+DtXUlKS7rvvviuu4dyjhg6HQy+88IKWLFmi3377Tbm5ucrNzVVQUJAkadeuXcrNzT3v+7Gfn5/uvvtuLViwQIMHD1ZSUpK2b99e7HQ0KidTAuC1116r1q1ba8CAARo6dKikwsPMPj4+2rhxowYOHKgpU6aYURoAoAoJCwi7pP7nHgEsUsu/1iUfAbwU8fHxio6O1r/+9S9FRUXJ6XSqRYsWysvLU0BAwAWXvdh8m80mwzDc2kq6yaMo2BV56aWX9PLLL2vWrFmKi4tTUFCQEhISXJ/IcbHtSoWnga+55hodPHhQCxYsUPfu3dWgQYOLLgfzmRIAN23apAULFujvf/+7EhMTNXDgQI0aNUoTJkzQhAkTzCgJAFAFXcpp2CLL9yzX9K+my2k45WXz0tT2UzWwycCLL3iZjh49ql27dmnevHnq1KmTJGnjxo2u+S1bttTrr7+uP/74o8SjgC1bttTatWv15z//ucT1165dW6mpqa7pPXv2lOoyqg0bNqh///66++67JRXe8LFnzx41a9ZMktSkSRMFBARo7dq1Gj16dInriIuLU9u2bfWvf/1Lixcv1quvvnrR7aJyMCUAtm/fXu3bt9crr7yid999VwsXLlSPHj3UsGFD3XvvvRoxYoTq1atnRmkAAA83sMlAdYjqoANZBxQdHK2IoIhy3V6NGjVUq1YtzZ8/X5GRkUpJSdGkSZNc84cOHarnn39eAwYMUGJioiIjI7Vt2zZFRUWpffv2mjp1qrp3766rrrpKd955pwoKCvTxxx+7Dph069ZNs2fP1g033CCn06mJEyfKx8fnonU1btxYy5Yt0+bNm1WjRg3NnDlTaWlprgDo7++viRMnasKECfL19VXHjh115MgR7dy5U6NGjXKtZ/To0XrkkUcUGBio2267rYx/eygvpt4FHBAQoBEjRujLL7/U7t27NXToUM2bN08xMTHq16+fmaUBADxYRFCE2kW0K/fwJ0leXl565513tHXrVrVo0ULjxo3T3/72N9d8X19fffrpp6pTp4769eunuLg4vfDCC7LbC09J33TTTVq6dKlWrlypa665Rt26dXO7U/ell15SdHS0OnfurLvuukuPP/64AgMDL1rXlClTdO2116p379666aabFBERoQEDBhTr85e//EVPP/20mjVrpiFDhujwYfdrLocOHSpvb2/ddddd8vf3v4LfFCqSzTj3wgETZWdna9GiRXryySd1/PhxORwOs0u6oMzMTIWGhiojI0MhISFmlwMAHuvUqVPat2+fYmJiCBmVzIEDB9SwYUNt2bJF1157rdnluFxon+H9uxJ8FZwkrVu3TgsWLNCyZctkt9s1ePBgt8PLAACgcsnPz1dqaqomTZqkG264oVKFP1ycaQHwwIEDevPNN/Xmm29q37596tChg1599VUNHjy42J1KAACgctm0aZO6du2qpk2b6r333jO7HFwiUwJgz5499cUXX6h27doaPny47r33Xv3pT38yoxQAAHAZbrrppmIfP4Oqw5QAGBAQoGXLlumWW25xXeQKAACAimFKAFy5cqUZmwUAAIBM/hgYAAAAVDwCIAAAgMUQAAEAACyGAAgAAGAxBEAAACqxhg0batasWWaXAQ9DAAQAALAYAiAAACgXDodDTqfT7DJQAgIgAMBy8tPSlPP1/1N+Wlq5bmfevHmqW7dusRB06623asSIEdq7d6/69++v8PBwVatWTe3atdNnn3122dubOXOm4uLiFBQUpOjoaD300EPKzs5267Np0yZ16dJFgYGBqlGjhnr37q1jx45JkpxOp2bMmKHGjRvLz89P9evX13PPPSdJ+vLLL2Wz2XT8+HHXupKSkmSz2fTrr79Kkt58801Vr15dH374oZo3by4/Pz/t379fW7ZsUc+ePRUWFqbQ0FB16dJF3333nVtdx48f1/3336/w8HD5+/urRYsW+vDDD5WTk6OQkJBiXzf3wQcfKCgoSFlZWZf9+7IyAiAAwFKOv/eefu7WXSkjR+rnbt11vBy/x/aOO+5Qenq6vvjiC1fbsWPHtHr1ag0bNkzZ2dnq16+fPvvsM23btk29e/dWfHy8UlJSLmt7Xl5eeuWVV/TDDz/o3//+tz7//HNNmDDBNT8pKUndu3dXbGysvvrqK23cuFHx8fFyOBySpMmTJ2vGjBmaMmWKkpOTtXjxYoWHh19SDSdOnFBiYqJef/117dy5U3Xq1FFWVpZGjBihDRs26Ouvv1aTJk3Ur18/V3hzOp3q27evNm/erP/+979KTk7WCy+8ILvdrqCgIN15551auHCh23YWLlyo22+/XcHBwZf1u7I6m+FBX+Q3Z84c/e1vf1NqaqpiY2M1a9YsderU6aLLFf011KJFCyUlJZV6e5mZmQoNDVVGRoZCQkKuoHIAwIWcOnVK+/btU0xMjPz9/V3t+wbdroL09FKvx3A45Cihvz0sTLZL+GpS77AwxSwrXXDs37+/wsLC9MYbb0iS5s+fr6lTp+rgwYMlfh1qbGysHnzwQT3yyCOSCm8CSUhIUEJCQqnrK7J06VI9+OCDSj895rvuukspKSnauHFjsb5ZWVmqXbu2Zs+erdGjRxeb/+WXX6pr1646duyYqlevLqkwULZu3Vr79u1Tw4YN9eabb+rPf/6zkpKS1KpVq/PW5XA4VKNGDS1evFi33HKLPv30U/Xt21e7du1S06ZNi/X/5ptv1KFDB6WkpCgqKkrp6emKiorSmjVr1KVLlxK3cb59RuL9W/KgI4BLlixRQkKCnnrqKW3btk2dOnVS3759L/pXVEZGhoYPH67u3btXUKUAgLJSkJ6ugt9/L/WjpPAnSY5LXM+lhM5hw4Zp2bJlys3NlSQtWrRId955p+x2u3JycjRhwgQ1b95c1atXV7Vq1fTjjz9e9hHAL774Qj179lTdunUVHBys4cOH6+jRo8rJyZF05ghgSXbt2qXc3Nwrfj/09fVVy5Yt3doOHz6sMWPGqGnTpgoNDVVoaKiys7Nd40xKSlK9evVKDH+SdN111yk2NlZvvfWWJOk///mP6tevr86dO19RrVZmyncBl4eZM2dq1KhRrr9aZs2apdWrV2vu3LlKTEw873IPPPCA7rrrLtntdr3//vsVVC0AoCx4h4VdUv+yPAJYWvHx8XI6nfroo4/Url07bdiwQTNnzpQkPfHEE1q9erX+/ve/q3HjxgoICNDtt9+uvLy8Uq+/yP79+9WvXz+NGTNG//d//6eaNWtq48aNGjVqlPLz8yVJAQEB513+QvOkwtPLknT2icOi9Z67HpvN5tY2cuRIHTlyRLNmzVKDBg3k5+en9u3bu8Z5sW1L0ujRozV79mxNmjRJCxcu1J///Odi20HpeUQAzMvL09atWzVp0iS39l69emnz5s3nXW7hwoXau3ev/vvf/+rZZ5+96HZyc3Ndf8FJhYeQAQDmKe1p2LMdf+89pT49VXI6JS8vRT4zXdVvv70cqisUEBCggQMHatGiRfr555/VtGlTtWnTRpK0YcMGjRw5UrfddpskKTs723VDxaX69ttvVVBQoJdeeskV1t599123Pi1bttTatWs1ffr0Yss3adJEAQEBWrt2bYmngGvXri1JSk1NVY0aNSSp1JdNbdiwQXPmzFG/fv0kSQcOHHCdli6q6+DBg9q9e/d5jwLefffdmjBhgl555RXt3LlTI0aMKNW2UTKPCIDp6elyOBzFLlQNDw9X2nnu8NqzZ48mTZqkDRs2yNu7dL+GxMTEEv+jAQBUHdVvv11BN96ovP0p8m1QXz4REeW+zWHDhik+Pl47d+7U3Xff7Wpv3Lixli9frvj4eNlsNk2ZMuWyPzblqquuUkFBgV599VXFx8dr06ZNeu2119z6TJ48WXFxcXrooYc0ZswY+fr66osvvtAdd9yhsLAwTZw4URMmTJCvr686duyoI0eOaOfOnRo1apQaN26s6OhoTZs2Tc8++6z27Nmjl156qVS1NW7cWP/5z3/Utm1bZWZm6oknnnA76telSxd17txZgwYN0syZM9W4cWP9+OOPstls6tOnjySpRo0aGjhwoJ544gn16tVL9erVu6zfEwp5zDWAkoodCjYMo8TDww6HQ3fddZemT59+3r80SjJ58mRlZGS4HgcOHLjimgEAFc8nIkJB119XIeFPkrp166aaNWvqp59+0l133eVqf/nll1WjRg116NBB8fHx6t27t6699trL2sY111yjmTNnasaMGWrRooUWLVpU7BKopk2b6tNPP9X27dt13XXXqX379vrf//7nOhAyZcoU/eUvf9HTTz+tZs2aaciQITp8+LAkycfHR2+//bZ+/PFHtWrVSjNmzCjV2TNJWrBggY4dO6bWrVvrnnvu0WOPPaY6deq49Vm2bJnatWunoUOHqnnz5powYYLr7uQio0aNUl5enu69997L+h3hDI+4CzgvL0+BgYFaunSp6zC6JI0dO1ZJSUlat26dW//jx4+rRo0abndfOZ1OGYYhu92uTz/9VN26dbvodrmLCAAqxoXu6IR1LFq0SGPHjtWhQ4fk6+t7wb7cBXxhHnEK2NfXV23atNGaNWvcAuCaNWvUv3//Yv1DQkK0Y8cOt7Y5c+bo888/13vvvaeYmJhyrxkAAJTOiRMntG/fPiUmJuqBBx64aPjDxXnMKeDx48fr9ddf14IFC7Rr1y6NGzdOKSkpGjNmjKTC07fDhw+XVHgnU4sWLdwederUcX3yeFBQkJlDAQCgmEWLFqlatWolPmJjY80ur1y9+OKLuuaaaxQeHq7JkyebXY5H8IgjgJI0ZMgQHT16VM8884xSU1PVokULrVq1Sg0aNJBUeNfS5X6uEgAAZrv11lt1/fXXlzjPx8engqupWNOmTdO0adPMLsOjeMQ1gGbhGgIAqBhcA4hLxTWAF+Yxp4ABAABQOgRAAECVwUkrlBb7yoURAAEAlV7RNW4nTpwwuRJUFUX7iqdfH3m5POYmEACA57Lb7apevbrrQ4kDAwP5HliUyDAMnThxQocPH1b16tXdPvMXZxAAAQBVQsTpb+0oCoHAhVSvXt21z6A4AiAAoEqw2WyKjIxUnTp1lJ+fb3Y5qMR8fHw48ncRBEAAQJVit9t5cweuEDeBAAAAWAwBEAAAwGIIgAAAABZDAAQAALAYAiAAAIDFEAABAAAshgAIAABgMQRAAAAAiyEAAgAAWAwBEAAAwGIIgAAAABZDAAQAALAYAiAAAIDFEAABAAAshgAIAABgMQRAAAAAiyEAAgAAWAwBEAAAwGIIgAAAABZDAAQAALAYAiAAAIDFEAABAAAshgAIAABgMQRAAAAAiyEAAgAAWAwBEAAAwGIIgAAAABZDAAQAALAYAiAAAIDFEAABAAAshgAIAABgMQRAAAAAiyEAAgAAWAwBEAAAwGIIgAAAABZDAAQAALAYAiAAAIDFeJtdAEq2KzVT6dm5alynmiJDA8wuBwAAeBACYCVjGIYmL9+hd7YckCR52aTEgXEa0q6+yZUBAABPwSngSubrX/5whT9JchrSk8t/UGrGSROrAgAAnoQAWMkYMoq1OQxDv6afMKEaAADgiQiAlUxMWJC8bO5tNpvUMCzQnIIAAIDHIQBWMpGhAUocGOcWAn3tXvKy2c6/EAAAwCUgAFZCQ9rV16ZJ3dS5aZgkKbfAqSnv/yDDKH56GAAA4FIRACupyNAAvXJna4VV85UkfZr8uz7+Ic3kqgAAgCcgAFZi1QN9Ne3WWNf00//bqYwT+SZWBAAAPAEBsJK7OS5SPZqFS5LSs3P13KpkkysCAABVHQGwkrPZbPq/AbGq5lf4md3vfntQm35ON7kqAABQlREAq4DI0ABN6nu1a3ry8h06mecwsSIAAFCVeVQAnDNnjmJiYuTv7682bdpow4YN5+27fPly9ezZU7Vr11ZISIjat2+v1atXV2C1l+au6+rruoY1JUkpf5zQy5/tNrkiAABQVXlMAFyyZIkSEhL01FNPadu2berUqZP69u2rlJSUEvuvX79ePXv21KpVq7R161Z17dpV8fHx2rZtWwVXXjpeXjYlDoqTr3fhS/b6hl/0/cHj5hYFAACqJJvhIR8ud/311+vaa6/V3LlzXW3NmjXTgAEDlJiYWKp1xMbGasiQIXr66adL1T8zM1OhoaHKyMhQSEjIZdV9qf75xc/62+qfJEnNIkO08pGO8rF7TI4HAKDcmfH+Xdl4RHLIy8vT1q1b1atXL7f2Xr16afPmzaVah9PpVFZWlmrWrHnePrm5ucrMzHR7VLT7OzfS1RHBkqRdqZmav/6XCq8BAABUbR4RANPT0+VwOBQeHu7WHh4errS00n148ksvvaScnBwNHjz4vH0SExMVGhrqekRHR19R3ZfDx+6lF29v6fqquH+s3aO9R7IrvA4AAFB1eUQALGI75/tyDcMo1laSt99+W9OmTdOSJUtUp06d8/abPHmyMjIyXI8DBw5ccc2Xo2W96hp1Y4wkKa/AqcnLd8jp9Igz+QAAoAJ4RAAMCwuT3W4vdrTv8OHDxY4KnmvJkiUaNWqU3n33XfXo0eOCff38/BQSEuL2MMu4nk0VXTNAkvTNvj/09paSb3YBAAA4l0cEQF9fX7Vp00Zr1qxxa1+zZo06dOhw3uXefvttjRw5UosXL9bNN99c3mWWqUBfbyXe1tI1/cKqH5WWccrEigAAQFXhEQFQksaPH6/XX39dCxYs0K5duzRu3DilpKRozJgxkgpP3w4fPtzV/+2339bw4cP10ksv6YYbblBaWprS0tKUkZFh1hAu2Y1NwnRHm3qSpKzcAv31/R/kITd1AwCAcuQxAXDIkCGaNWuWnnnmGV1zzTVav369Vq1apQYNGkiSUlNT3T4TcN68eSooKNDDDz+syMhI12Ps2LFmDeGyPHVzM4VV85Mkfbbrd63aUbqbXgAAgHV5zOcAmqGyfI7QR9+n6uHF30mSwqr56rPxXVQ90Ne0egAAqMwqy/u3mTzmCKCV9YuLUM/mhTe7pGfn6bmPdplcEQAAqMwIgB7AZrPp//q3ULCftyRp6daD2rgn3eSqAABAZUUA9BARof6a1O9q1/TkFd/rRF6BiRUBAIDKigDoQYa2q6/rYgq/yu7AHyf18prdJlcEAAAqIwKgB/HysumFgXHy9S58Wd/YuE/bDxw3tygAAFDpEAA9TKPa1TS2exNJktOQJi77XvkOp8lVAQCAyoQA6IHu79xIzSILb2v/MS1L89f/YnJFAACgMiEAeiAfu5dmDIqTl61w+h9r92jvkWxziwIAAJUGAdBDtaxXXaM7NZIk5RU4NWnZ93I6+cxvAABAAPRo43o0Vf2agZKkLb8e0+JvUi6yBAAAsAICoAcL8LUrcWCca/qFj39UasZJEysCAACVAQHQw3VsHKbBbetJkrJzCzTl/R/E1z8DAGBtBEALeKpfc4VV85MkfbbrsD7akWpyRQAAwEwEQAsIDfTRM/1jXdPTVu7UsZw8EysCAABmIgBaRN8WEerVPFySlJ6dp2c/2mVyRQAAwCwEQIuw2Wx6pn8LBft5S5KWfXdQG/YcMbkqAABgBgKghUSE+mtyv2au6cnLd+hEXoGJFQEAADMQAC3mznbRuj6mpiTp4LGTmvnpbpMrAgAAFY0AaDFeXjYlDoyTr3fhS79g0z5tP3Dc3KIAAECFIgBaUKPa1ZTQo4kkyWlIE5d9r7wCp8lVAQCAikIAtKj7OjVS88gQSdKPaVmav36vyRUBAICKQgC0KB+7l2YMaikvW+H0K2t/1s+Hs80tCgAAVAgCoIXF1QvVfZ0aSZLyHE5NXv69nE6+Jg4AAE9HALS4hB5N1aBWoCRpy6/HtOibFJMrAgAA5Y0AaHEBvnYl3hbnmp7x8Y9KzThpYkUAAKC8EQChDo3DNKRttCQpO7dAf13xgwyDU8EAAHgqAiAkSU/2a6bawX6SpLU/HtaH36eaXBEAACgvBEBIkkIDffTMrbGu6Wkrd+pYTp6JFQEAgPJCAIRL37hI9Y4NlyQdzcnT/32UbHJFAACgPBAA4eaZ/i0U7O8tSVr+3W9av/uIyRUBAICyRgCEm/AQfz3Zr5lr+skVO5STW2BiRQAAoKwRAFHMne2idUOjmpKkg8dO6qVPd5tcEQAAKEsEQBRjs9mUOLCl/LwLd4+Fm/dpW8oxk6sCAABlhQCIEsWEBSmhR1NJkmFIk5btUF6B0+SqAABAWSAA4rzu6xSj2KgQSdJPv2fptXV7Ta4IAACUBQIgzsvb7qUZg1rK7mWTJM3+/Gf9fDjL5KoAAMCVIgDiglrUDdXoTjGSpDyHU5OW7ZDTydfEAQBQlREAcVHjejRVg1qBkqRv9x/Tf//ffpMrAgAAV4IAiIvy97ErcWCca3rGxz/q0PGTJlYEAACuBAEQpdLhqjDd2S5akpST59Bf3/9BhsGpYAAAqiICIEptcr9mqh3sJ0n6/MfDWrn9kMkVAQCAy0EARKmFBvjo//rHuqanf5CsP3LyTKwIAABcDgIgLkmfFpHqExshSfojJ0/PfphsckUAAOBSEQBxyab3j1Wwv7ckafm23/TlT4dNrggAAFwKAiAuWXiIv57q18w1/dSKH5STW2BiRQAA4FIQAHFZhrSLVvtGtSRJvx0/qb9/+pPJFQEAgNIiAFZWGb9J+9YXPldCNptNiQPj5OdduAu9uflXfZdyzOSqAABAaRAAK6Nlo6WXY6V/x0uzWkhb3zS7ohI1DAvSuJ5NJUmGIU1a9r3yCpwmVwUAAC6GAFjZZPwm7Vgq6fSHLBtO6YOx0tyO0v8ekb6eW3hkMOeoqWUWGX1jjGKjQiRJu3/P1twv95pcEQAAuBhvswvAOdL3lNz++w+Fj7NVi5DCY90fYU0lb7/yr/M0b7uXZgxqqf7/3CSH09DsL/aoX1yEmoQHV1gNAADg0hAAK5uwxpLNq/DI38VkpxU+9q490+blLdVqcjoQNpfCWxT+HFJXstnKpeQWdUN1X6dGem3dXuU7DE1c9r3eG9NBXl7lsz0AAHBlbAZf6HrZMjMzFRoaqoyMDIWEhJTdir97S/ogQTIcks0uxc+SWgySDv94+kjgTulwcuHPJ0t544Vf6FmhMLYwGNZpJvmVzZG6U/kO9Zm1Xr8ePSFJmn5rrEZ0aFgm6wYAoCyV2/t3FUIAvALlugNl/Cb98YtUs5EUWrfkPoYhZaVKvye7B8MjP0nO/NJtp3qD00cJTwfDOrFSraskL/sll/zV3qMa+q+vJUlBvnZ9Or6L6lYPuOT1AABQngiABMArUml3oII86ejPhYHw9x9OHy3cKWWW8iNlvP2l2le7X1tYJ1aqVvuii05e/r3e/uaAJKnrn2prwch2spXTqWcAAC5HpX3/rkAEwCtQ5Xagk8dOHy08OxgmS/k5pVs+qM45obB5YVD08Xd1yTiZr54z1+lwVq4k6R93XqP+15znCCYAACaocu/f5YAAeAU8YgdyOqXj+0+Hwp3S4dPPR/fK9VE0F2KzS7Uau11buO54bY1YkSbJpqb+mXquS4DqN4lTeL2ryns05SfjN+mPvVLNq85/Sr4qYByVi6eMA5WLp+xX5TgOj3j/vkIeFQDnzJmjv/3tb0pNTVVsbKxmzZqlTp06nbf/unXrNH78eO3cuVNRUVGaMGGCxowZU+rtefQOlHdCOvKjezBM+0E6+UepFj/pFaTfC6qpge132WyS05C+9b5Wx4KbytvuJV+7V+Gzt5dr2sfb7mrzOT3t4+prk81W9LGVp08pu04tn29al9j/PNMHt0rJ76swENuk2Nuk6OsKf7bZznrWmemzfy7xWReYd872r2j5s9r2fiZ9/VrhOGw26YaHpaZ9Cn+2eZ3u63XOtO0i88+e1kXmX2H/onF/91bhZ2MazsL2W2ZJre8unHY6Cp8NZ+FNVIaz8FrZEtuL+hvnaT+9bIntRf2Ny99uyv+TfnjvzH7VaojUsFPhnfznPuxnT/ucfrafnnfO9NnzXfO83X+HZc3qgaPotXbmS84CyZF/Ztpxus3VXnDO9Om+rp8LJEdRn/wS1lXCes9e15Hd0sFvztQW2UqqXr+wxqJaZZTw7LzAvIstW9pnlbKfUzqVKZ1IPzOOW1+Vrh1+aa/nBXj0+3cpeUwAXLJkie655x7NmTNHHTt21Lx58/T6668rOTlZ9evXL9Z/3759atGihe677z498MAD2rRpkx566CG9/fbbGjRoUKm2abkdyDCk7N/PhMKiYHjkJ8mRZ3Z1AC7G66xAeG5A9LK7z7eXEERLWvbYfhkHv5FNp6Ns/RsKzwpIxd/wpeJv9pfcpvJZX1aajD9+PjOO0GjJP/SsoHVuUDsntKF82exSwo4y+wPDcu/fJfCYAHj99dfr2muv1dy5c11tzZo104ABA5SYmFis/8SJE7Vy5Urt2rXL1TZmzBht375dX331Vam2yQ50miO/8JTxWXci56Vske+pyvFtJQCAinSBsxMXfVbhEdCSrk0f8aEUc/6zepeC928P+SDovLw8bd26VZMmTXJr79WrlzZv3lziMl999ZV69erl1ta7d2+98cYbys/Pl4+PT7FlcnNzlZub65rOzMwsg+o9gN1HqnN14SPudknSsYN7FfavNrLbzvx94TBsSuk2Wz4h4TqVX6BT+Y7CR55DpwoKCp/z3R95BQ6dzHMot6BwOjf/zHPhibOi9Rc+nzk5apzzfOH28y1fQ5l61udNeZ0zjun5I3RcQbLJkO10/6KfJclmM9y2dXafou24T5+z/FnThX3O/vncdbr3KWn5YFuO7rV/orM/m9tp2PQfRw+dlL8kQ16nl/FyLes+fd52m1GK5SUvOU/X43Sb9lLhh56fmTZcv79zt++rfDW37Xc7k2kY0nYjRrnykyGbHEbhmgzZ5JCXnKfXfOa56Oez2o3CZ8fpLTlPL2uoqP3cdRb2K9qW+/q9zrutonUGGzma4rPIbb9yGjbNKBiiE/KXtxyyyylvOQoftsJpHzlkP91WOL9A3nLKbnPI++xpOc70tZ0zfXp+0brttuLrPXtZK8sz7MqVrxzyUr7sKpB34c+GXQ7ZT7ed+dkhu/KNwraCc+YVnNPu9jDOLH92e77scpwzL/8863TIrlBl6T++LxT7d3dA7nQdVk3XvziF/zXprOmS/jVybz/7X6hz22Ur+q+6bC4xCDeOapPfY27jKDC8dNQnSuFlsgVIHhIA09PT5XA4FB7uvmuEh4crLS2txGXS0tJK7F9QUKD09HRFRkYWWyYxMVHTp08vu8I9WHi9q/RNy2m69vvp8rY5VWB46buWU3Vdl7vLZP2GYehUvlM5eQXKyS1Qdm6BTuQ5Cp9zHcrJLXDNy8k7PX1Ou6v/6ee8gpLf7AoKvPW89xuucTxZMErvOruWyTgq0m4juvg4HFVvHIPtX3jEOHIKAqrAOAy3IHomSBa2RdiOaqnvM8UCx915k3VE1U+vwT00FP58bug4608c49xlii+rEpYtfb/i0+H6Q1/4/aVY4OicO0tpqlUGv8eKM7lgdLH9aocal+9Gy/g8YppqlTiO23KrEwDLkEcEwCLnft6cYRgX/Ay6kvqX1F5k8uTJGj9+vGs6MzNT0dHRl1uux7tuUIJ+vz5e6ft/VFiDq3VdGd4FbLPZFOBrV4CvXWHVyua7j/MdTp3IdSg7r0AnTofKA8dOaOzb0npHSzX0+l2/OsP1u62WJve9WqEBPnIakiHj9JuWJMOQIcnpLHwuai/at5yGcVbbmWVVbBnDbdnibWdNn2edhnFmfdm5+Xp3W1f3caiW+l8TqQCfwn8GXJdDnf7X/Mz0Gef2OefJNc6SlzlPn7M6F9v2Ods7mefQu3vcx5GmWurUJEx+3iV9eHnxd6aSLnop6f3rfFfHlNz30taZm+/Qu78WH8d1DWvIz+fCH8J+ORftGCVWc+XbyC1waPLB4m/UudE3qvZZr8eFtn+hbV2wjAsud+EBnLvNvILampxWfBy16zZSXW+vkldy3nVfeRq63DXkFTj17qHi+1XzyBD5XuI4Sqs8riHLK3Dq3VT3cRyxhWlcWGA5bM26PCIAhoWFyW63Fzvad/jw4WJH+YpERESU2N/b21u1apX8F5+fn5/8/MombFhFeL2rqszHv/jYvRQa6KXQwDOn/1vXr6GTeQ49ufwHpTlryW6z6YWBLTSkXfEbiyq7GxrV8ohxLNmS4jaOGYzDVEu2RKvL8laKtqXpgBGhxwZ20YtVchz1PWQcnrJfuY/j+YEtFBnKN0uVJY+6CaRNmzaaM2eOq6158+bq37//eW8C+eCDD5ScnOxqe/DBB5WUlMRNICgmNeOkfk0/oYZhgVX6HyHGUbkwjsqFcVQu5TkO3r89KAAWfQzMa6+9pvbt22v+/Pn617/+pZ07d6pBgwaaPHmyfvvtN7311luSznwMzAMPPKD77rtPX331lcaMGcPHwAAA4OF4//aQU8CSNGTIEB09elTPPPOMUlNT1aJFC61atUoNGjSQJKWmpiolJcXVPyYmRqtWrdK4ceP0z3/+U1FRUXrllVdKHf4AAACqKo85AmgG/oIAAKDq4f1bKp/bggAAAFBpEQABAAAshgAIAABgMQRAAAAAiyEAAgAAWAwBEAAAwGIIgAAAABZDAAQAALAYAiAAAIDFeMxXwZmh6EtUMjMzTa4EAACUVtH7tpW/DI0AeAWysrIkSdHR0SZXAgAALlVWVpZCQ0PNLsMUfBfwFXA6nTp06JCCg4Nls9nMLqdSyszMVHR0tA4cOGDZ71usTHg9Khdej8qF16NyKc/XwzAMZWVlKSoqSl5e1rwajiOAV8DLy0v16tUzu4wqISQkhH9QKxFej8qF16Ny4fWoXMrr9bDqkb8i1oy9AAAAFkYABAAAsBgCIMqVn5+fpk6dKj8/P7NLgXg9Khtej8qF16Ny4fUoX9wEAgAAYDEcAQQAALAYAiAAAIDFEAABAAAshgAIAABgMQRAlLnExES1a9dOwcHBqlOnjgYMGKCffvrJ7LJwWmJiomw2mxISEswuxdJ+++033X333apVq5YCAwN1zTXXaOvWrWaXZUkFBQX661//qpiYGAUEBKhRo0Z65pln5HQ6zS7NEtavX6/4+HhFRUXJZrPp/fffd5tvGIamTZumqKgoBQQE6KabbtLOnTvNKdaDEABR5tatW6eHH35YX3/9tdasWaOCggL16tVLOTk5ZpdmeVu2bNH8+fPVsmVLs0uxtGPHjqljx47y8fHRxx9/rOTkZL300kuqXr262aVZ0owZM/Taa69p9uzZ2rVrl1588UX97W9/06uvvmp2aZaQk5OjVq1aafbs2SXOf/HFFzVz5kzNnj1bW7ZsUUREhHr27KmsrKwKrtSz8DEwKHdHjhxRnTp1tG7dOnXu3NnsciwrOztb1157rebMmaNnn31W11xzjWbNmmV2WZY0adIkbdq0SRs2bDC7FEi65ZZbFB4erjfeeMPVNmjQIAUGBuo///mPiZVZj81m04oVKzRgwABJhUf/oqKilJCQoIkTJ0qScnNzFR4erhkzZuiBBx4wsdqqjSOAKHcZGRmSpJo1a5pcibU9/PDDuvnmm9WjRw+zS7G8lStXqm3btrrjjjtUp04dtW7dWv/617/MLsuybrzxRq1du1a7d++WJG3fvl0bN25Uv379TK4M+/btU1pamnr16uVq8/PzU5cuXbR582YTK6v6vM0uAJ7NMAyNHz9eN954o1q0aGF2OZb1zjvv6LvvvtOWLVvMLgWSfvnlF82dO1fjx4/Xk08+qW+++UaPPfaY/Pz8NHz4cLPLs5yJEycqIyNDV199tex2uxwOh5577jkNHTrU7NIsLy0tTZIUHh7u1h4eHq79+/ebUZLHIACiXD3yyCP6/vvvtXHjRrNLsawDBw5o7Nix+vTTT+Xv7292OZDkdDrVtm1bPf/885Kk1q1ba+fOnZo7dy4B0ARLlizRf//7Xy1evFixsbFKSkpSQkKCoqKiNGLECLPLgwpPDZ/NMIxibbg0BECUm0cffVQrV67U+vXrVa9ePbPLsaytW7fq8OHDatOmjavN4XBo/fr1mj17tnJzc2W3202s0HoiIyPVvHlzt7ZmzZpp2bJlJlVkbU888YQmTZqkO++8U5IUFxen/fv3KzExkQBosoiICEmFRwIjIyNd7YcPHy52VBCXhmsAUeYMw9Ajjzyi5cuX6/PPP1dMTIzZJVla9+7dtWPHDiUlJbkebdu21bBhw5SUlET4M0HHjh2LfTTS7t271aBBA5MqsrYTJ07Iy8v97dBut/MxMJVATEyMIiIitGbNGldbXl6e1q1bpw4dOphYWdXHEUCUuYcffliLFy/W//73PwUHB7uu4QgNDVVAQIDJ1VlPcHBwsesvg4KCVKtWLa7LNMm4cePUoUMHPf/88xo8eLC++eYbzZ8/X/Pnzze7NEuKj4/Xc889p/r16ys2Nlbbtm3TzJkzde+995pdmiVkZ2fr559/dk3v27dPSUlJqlmzpurXr6+EhAQ9//zzatKkiZo0aaLnn39egYGBuuuuu0ys2gMYQBmTVOJj4cKFZpeG07p06WKMHTvW7DIs7YMPPjBatGhh+Pn5GVdffbUxf/58s0uyrMzMTGPs2LFG/fr1DX9/f6NRo0bGU089ZeTm5ppdmiV88cUXJb5njBgxwjAMw3A6ncbUqVONiIgIw8/Pz+jcubOxY8cOc4v2AHwOIAAAgMVwDSAAAIDFEAABAAAshgAIAABgMQRAAAAAiyEAAgAAWAwBEAAAwGIIgAAAABZDAASAMmSz2fT++++bXQYAXBABEIDHGDlypGw2W7FHnz59zC4NACoVvgsYgEfp06ePFi5c6Nbm5+dnUjUAUDlxBBCAR/Hz81NERITbo0aNGpIKT8/OnTtXffv2VUBAgGJiYrR06VK35Xfs2KFu3bopICBAtWrV0v3336/s7Gy3PgsWLFBsbKz8/PwUGRmpRx55xG1+enq6brvtNgUGBqpJkyZauXJl+Q4aAC4RARCApUyZMkWDBg3S9u3bdffdd2vo0KHatWuXJOnEiRPq06ePatSooS1btmjp0qX67LPP3ALe3Llz9fDDD+v+++/Xjh07tHLlSjVu3NhtG9OnT9fgwYP1/fffq1+/fho2bJj++OOPCh0nAFyQAQAeYsSIEYbdbjeCgoLcHs8884xhGIYhyRgzZozbMtdff73x4IMPGoZhGPPnzzdq1KhhZGdnu+Z/9NFHhpeXl5GWlmYYhmFERUUZTz311HlrkGT89a9/dU1nZ2cbNpvN+Pjjj8tsnABwpbgGEIBH6dq1q+bOnevWVrNmTdfP7du3d5vXvn17JSUlSZJ27dqlVq1aKSgoyDW/Y8eOcjqd+umnn2Sz2XTo0CF17979gjW0bNnS9XNQUJCCg4N1+PDhyx0SAJQ5AiAAjxIUFFTslOzF2Gw2SZJhGK6fS+oTEBBQqvX5+PgUW9bpdF5STQBQnrgGEIClfP3118Wmr776aklS8+bNlZSUpJycHNf8TZs2ycvLS02bNlVwcLAaNmyotWvXVmjNAFDWOAIIwKPk5uYqLS3Nrc3b21thYWGSpKVLl6pt27a68cYbtWjRIn3zzTd64403JEnDhg3T1KlTNWLECE2bNk1HjhzRo48+qnvuuUfh4eGSpGnTpmnMmDGqU6eO+vbtq6ysLG3atEmPPvpoxQ4UAK4AARCAR/nkk08UGRnp1vanP/1JP/74o6TCO3TfeecdPfTQQ4qIiNCiRYvUvHlzSVJgYKBWr16tsWPHql27dgoMDNSgQYM0c+ZM17pGjBihU6dO6eWXX9bjjz+usLAw3X777RU3QAAoAzbDMAyziwCAimCz2bRixQoNGDDA7FIAwFRcAwgAAGAxBEAAAACL4RpAAJbBFS8AUIgjgAAAABZDAAQAALAYAiAAAIDFEAABAAAshgAIAABgMQRAAAAAiyEAAgAAWAwBEAAAwGIIgAAAABbz/wHrwnLMdbdhlgAAAABJRU5ErkJggg==" alt="Learning Curve"> | |
| </div> | |
| </div> | |
| <div style="display: flex;"> | |
| <div class="section class_dist"> | |
| <h2>Class Distribution</h2> | |
| <pre> Count Percentage | |
| class | |
| 1 1876 50.35 | |
| 0 1850 49.65</pre> | |
| <h3>Additional Metrics</h3> | |
| <ul> | |
| <li>Total Samples: 3726</li> | |
| <li>Imbalance Ratio: 1.01</li> | |
| </ul> | |
| </div> | |
| <div class="section"> | |
| <h2>Classification Report</h2> | |
| <pre> precision recall f1-score support | |
| Class 0 0.9946 1.0000 0.9973 370 | |
| Class 1 1.0000 0.9947 0.9973 376 | |
| accuracy 0.9973 746 | |
| macro avg 0.9973 0.9973 0.9973 746 | |
| weighted avg 0.9973 0.9973 0.9973 746 | |
| </pre> | |
| <h3>Metrics</h3> | |
| <div class="metrics"> | |
| <ul> | |
| <li>True Positives (TP): 374</li> | |
| <li>True Negatives (TN): 370</li> | |
| </ul> | |
| <ul> | |
| <li>False Positives (FP): 0</li> | |
| <li>False Negatives (FN): 2</li> | |
| </ul> | |
| </div> | |
| </div> | |
| <div class="section confusion-matrix"> | |
| <h2>Confusion Matrix</h2> | |
| <img src="data:image/png;base64,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" alt="Confusion Matrix"> | |
| </div> | |
| </div> | |
| </div> | |
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