Saved figures and writing the first version of model evaluations part
This commit is contained in:
@@ -16,17 +16,13 @@
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"ename": "TypeError",
|
||||
"evalue": "cannot unpack non-iterable DecisionTreeClassifier object",
|
||||
"ename": "",
|
||||
"evalue": "",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"\u001b[31m---------------------------------------------------------------------------\u001b[39m",
|
||||
"\u001b[31mTypeError\u001b[39m Traceback (most recent call last)",
|
||||
"\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[18]\u001b[39m\u001b[32m, line 46\u001b[39m\n\u001b[32m 41\u001b[39m model = Pipeline([\n\u001b[32m 42\u001b[39m (DecisionTreeClassifier(random_state=\u001b[32m42\u001b[39m)) \u001b[38;5;66;03m# Train Decision Tree Regressor\u001b[39;00m\n\u001b[32m 43\u001b[39m ])\n\u001b[32m 45\u001b[39m \u001b[38;5;66;03m# Train the model\u001b[39;00m\n\u001b[32m---> \u001b[39m\u001b[32m46\u001b[39m \u001b[43mmodel\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 47\u001b[39m y_pred = model.predict(X_val)\n\u001b[32m 49\u001b[39m \u001b[38;5;66;03m# Visualize the decision tree\u001b[39;00m\n",
|
||||
"\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",
|
||||
"\u001b[36mFile \u001b[39m\u001b[32m~/Documents/MLP/Projects/MLPproject/.venv/lib/python3.12/site-packages/sklearn/pipeline.py:654\u001b[39m, in \u001b[36mPipeline.fit\u001b[39m\u001b[34m(self, X, y, **params)\u001b[39m\n\u001b[32m 647\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m _routing_enabled() \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m.transform_input \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[32m 648\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[32m 649\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mThe `transform_input` parameter can only be set if metadata \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 650\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mrouting is enabled. You can enable metadata routing using \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 651\u001b[39m \u001b[33m\"\u001b[39m\u001b[33m`sklearn.set_config(enable_metadata_routing=True)`.\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 652\u001b[39m )\n\u001b[32m--> \u001b[39m\u001b[32m654\u001b[39m routed_params = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_check_method_params\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmethod\u001b[49m\u001b[43m=\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mfit\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mprops\u001b[49m\u001b[43m=\u001b[49m\u001b[43mparams\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 655\u001b[39m Xt = \u001b[38;5;28mself\u001b[39m._fit(X, y, routed_params, raw_params=params)\n\u001b[32m 656\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m _print_elapsed_time(\u001b[33m\"\u001b[39m\u001b[33mPipeline\u001b[39m\u001b[33m\"\u001b[39m, \u001b[38;5;28mself\u001b[39m._log_message(\u001b[38;5;28mlen\u001b[39m(\u001b[38;5;28mself\u001b[39m.steps) - \u001b[32m1\u001b[39m)):\n",
|
||||
"\u001b[36mFile \u001b[39m\u001b[32m~/Documents/MLP/Projects/MLPproject/.venv/lib/python3.12/site-packages/sklearn/pipeline.py:454\u001b[39m, in \u001b[36mPipeline._check_method_params\u001b[39m\u001b[34m(self, method, props, **kwargs)\u001b[39m\n\u001b[32m 449\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m routed_params\n\u001b[32m 450\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m 451\u001b[39m fit_params_steps = Bunch(\n\u001b[32m 452\u001b[39m **{\n\u001b[32m 453\u001b[39m name: Bunch(**{method: {} \u001b[38;5;28;01mfor\u001b[39;00m method \u001b[38;5;129;01min\u001b[39;00m METHODS})\n\u001b[32m--> \u001b[39m\u001b[32m454\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m name, step \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m.steps\n\u001b[32m 455\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m step \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[32m 456\u001b[39m }\n\u001b[32m 457\u001b[39m )\n\u001b[32m 458\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m pname, pval \u001b[38;5;129;01min\u001b[39;00m props.items():\n\u001b[32m 459\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[33m\"\u001b[39m\u001b[33m__\u001b[39m\u001b[33m\"\u001b[39m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m pname:\n",
|
||||
"\u001b[31mTypeError\u001b[39m: cannot unpack non-iterable DecisionTreeClassifier object"
|
||||
"\u001b[1;31mRunning cells with '.venv (Python 3.13.7)' requires the ipykernel package.\n",
|
||||
"\u001b[1;31mInstall 'ipykernel' into the Python environment. \n",
|
||||
"\u001b[1;31mCommand: '/home/jaknyst/Documents/MLPproject/.venv/bin/python -m pip install ipykernel -U --force-reinstall'"
|
||||
]
|
||||
}
|
||||
],
|
||||
@@ -598,7 +594,7 @@
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.12.12"
|
||||
"version": "3.13.7"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
||||
Reference in New Issue
Block a user