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 +1,271 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "toc": true
+   },
+   "source": [
+    "# WS 06 Klassifikation - RandomForestClassifier"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "* untersuchen Sie die folgenden Tuning-Parameter von RandomForestClassifier in Bezug auf die erreichte Performance (accuracy_score) mit dem vorbereiteten Dataset:\n",
+    "  * n_estimators als `range(100, 500, 50)`\n",
+    "  * max_features als `range(1, 11)`\n",
+    "  * min_impurity_decrease als `np.arange(0, 0.1, 0.01)`\n",
+    "* wie wirkt sich der random_state aus?\n",
+    "* welche der ausserdem zur Verfügung stehenden Parameter sind keine Tuning Parameter? Konsultieren Sie dazu die (Online-) Dokumentation"
+   ]
+  },
+  {
+   "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",
+    "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('bank_data_prep.csv', target='y', seed=1234)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.ensemble import RandomForestClassifier"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "n_estimators:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "100\n",
+      "150\n",
+      "200\n",
+      "250\n",
+      "300\n",
+      "350\n",
+      "400\n",
+      "450\n"
+     ]
+    }
+   ],
+   "source": [
+    "model = RandomForestClassifier()\n",
+    "scores = []\n",
+    "params = range(100, 500, 50)\n",
+    "\n",
+    "for param in params:\n",
+    "    print(param)\n",
+    "    ## tbd\n",
+    "    \n",
+    "\n",
+    "## tbd\n",
+    "#fig = sns.lineplot(x=params, y=scores)\n",
+    "#...\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "max_features:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1\n",
+      "2\n",
+      "3\n",
+      "4\n",
+      "5\n",
+      "6\n",
+      "7\n",
+      "8\n",
+      "9\n",
+      "10\n"
+     ]
+    }
+   ],
+   "source": [
+    "model = RandomForestClassifier()\n",
+    "scores = []\n",
+    "params = range(1, 11)\n",
+    "\n",
+    "for param in params:\n",
+    "    print(param)\n",
+    "    ## tbd\n",
+    "    \n",
+    "    \n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "min_impurity_decrease:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.0\n",
+      "0.01\n",
+      "0.02\n",
+      "0.03\n",
+      "0.04\n",
+      "0.05\n",
+      "0.06\n",
+      "0.07\n",
+      "0.08\n",
+      "0.09\n"
+     ]
+    }
+   ],
+   "source": [
+    "model = RandomForestClassifier()\n",
+    "scores = []\n",
+    "params = np.arange(0, 0.1, 0.01)\n",
+    "\n",
+    "for param in params:\n",
+    "    print(param)\n",
+    "    ## tbd\n",
+    "    \n",
+    "    \n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Fazit:**\n",
+    "* tbd\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "keine Tuning Parameter sind hier:\n",
+    "* tbd\n",
+    "\n",
+    "\n"
+   ]
+  }
+ ],
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+   "pygments_lexer": "ipython3",
+   "version": "3.11.7"
+  },
+  "toc": {
+   "base_numbering": "2.2",
+   "nav_menu": {},
+   "number_sections": true,
+   "sideBar": true,
+   "skip_h1_title": false,
+   "title_cell": "WS 09 Klassifikation - RandomForestClassifier",
+   "title_sidebar": "Contents",
+   "toc_cell": true,
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+}