refactor: move things around

2026-05-21 14:16:30 +02:00
parent 2fce3281a3
commit 41e15ed275
124 changed files with 404226 additions and 0 deletions
@@ -0,0 +1,198 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "toc": true
+   },
+   "source": [
+    "# WS 09 Tune AdaBoostRegressor"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "* es wurde festgestellt, dass z.B. AdaBoostRegressor unter Standard-Parametrisierung ein unbrauchbares Ergebnis liefert\n",
+    "* untersuchen Sie das Potential von Parameter-Tuning für diesen Regressor\n",
+    "* konzentrieren Sie sich auf folgende Parameter\n",
+    "  * learning_rate, Parameter von AdaBoostRegressor\n",
+    "  * max_depth, interner Parameter des Basis-Estimators, hier DecisionTreeRegressor\n",
+    "* falls Zeit übrig, untersuchen Sie noch andere Regressoren Ihrer Wahl dahingehend"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "## prepare env, read and prepare data\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns; sns.set()\n",
+    "\n",
+    "codepath = '../2_code' ## for import of user defined module\n",
+    "datapath = '../3_data'\n",
+    "#codepath = '.././2_code' ## for import of user defined module\n",
+    "#datapath = '../../3_data'\n",
+    "\n",
+    "from sys import path; path.insert(1, codepath)\n",
+    "from os import chdir; chdir(datapath)\n",
+    "\n",
+    "from bfh_cas_pml import prep_data\n",
+    "X_train, X_test, y_train, y_test = prep_data('melb_data_prep.csv', target='Price', seed=1234)\n",
+    "\n",
+    "from bfh_cas_pml import test_regression_model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2020-04-08T10:06:45.098899Z",
+     "start_time": "2020-04-08T10:06:44.257283Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "R2 = -0.3023\n"
+     ]
+    }
+   ],
+   "source": [
+    "## baseline\n",
+    "from sklearn.ensemble import AdaBoostRegressor\n",
+    "this_model = test_regression_model(\n",
+    "    AdaBoostRegressor(random_state=1234), \n",
+    "    X_train, y_train, X_test, y_test,\n",
+    "    show_plot=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "## tune learning_rate\n",
+    "## tbd: find parameter range here\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "## tune max_depth\n",
+    "from sklearn.tree import DecisionTreeRegressor\n",
+    "## tbd: find parameter range here\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "## best combination of single parameters\n",
+    "## tbd\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Fazit**:\n",
+    "* tbd"
+   ]
+  }
+ ],
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+   "title_cell": "WS 11 Regression - mit FE - solution",
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