From 5f0e9bc9a9cfefa164a39b5a536c4049c2ab0321 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Pawe=C5=82=20Sk=C3=B3rzewski?= <pawel.skorzewski@amu.edu.pl>
Date: Thu, 24 Mar 2022 10:35:07 +0100
Subject: [PATCH] Laboratoria 4 - ewaluacja

---
 lab/04_scikit-learn.ipynb | 17 ++++++++++++-----
 1 file changed, 12 insertions(+), 5 deletions(-)

diff --git a/lab/04_scikit-learn.ipynb b/lab/04_scikit-learn.ipynb
index 8284a61..a8bd380 100644
--- a/lab/04_scikit-learn.ipynb
+++ b/lab/04_scikit-learn.ipynb
@@ -31,7 +31,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
@@ -47,7 +47,8 @@
       " [409340.86981766]\n",
       " [278401.700237  ]\n",
       " [301680.27997255]\n",
-      " [281051.71865054]]\n"
+      " [281051.71865054]]\n",
+      "Błąd średniokwadratowy wynosi  39595039990.2324\n"
      ]
     }
    ],
@@ -57,6 +58,8 @@
     "\n",
     "from sklearn.linear_model import LinearRegression  # Model regresji liniowej z biblioteki scikit-learn\n",
     "\n",
+    "from sklearn.metrics import mean_squared_error\n",
+    "\n",
     "\n",
     "FEATURES = [\n",
     "    'Powierzchnia w m2',\n",
@@ -78,7 +81,6 @@
     "\n",
     "# Wczytanie danych\n",
     "data = pd.read_csv(dataset_filename, header=0, sep='\\t')\n",
-    "columns = data.columns[1:]  # wszystkie kolumny oprócz pierwszej (\"cena\")\n",
     "data = data[FEATURES + ['cena']]  # wybór cech\n",
     "data = preprocess(data)  # wstępne przetworzenie danych\n",
     "\n",
@@ -98,7 +100,12 @@
     "x_test = pd.DataFrame(data_test[FEATURES])\n",
     "y_predicted = model.predict(x_test)  # predykcja wyników na podstawie modelu\n",
     "\n",
-    "print(y_predicted[:10])  # Pierwsze 10 wyników"
+    "print(y_predicted[:10])  # Pierwsze 10 wyników\n",
+    "\n",
+    "# Ewaluacja\n",
+    "mse = mean_squared_error(y_predicted, y_expected)  # Błąd średniokwadratowy na zbiorze testowym\n",
+    "\n",
+    "print(\"Błąd średniokwadratowy wynosi \", mse)"
    ]
   },
   {
@@ -126,7 +133,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.3"
+   "version": "3.7.6"
   },
   "livereveal": {
    "start_slideshow_at": "selected",