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Laboratoria 4 - ewaluacja

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Paweł Skórzewski 2022-03-24 10:35:07 +01:00
parent 3e4d0e7a93
commit 5f0e9bc9a9
1 changed files with 12 additions and 5 deletions
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lab/04_scikit-learn.ipynb
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@ -31,7 +31,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 1, "execution_count": 2,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
@ -47,7 +47,8 @@
" [409340.86981766]\n", " [409340.86981766]\n",
" [278401.700237 ]\n", " [278401.700237 ]\n",
" [301680.27997255]\n", " [301680.27997255]\n",
" [281051.71865054]]\n" " [281051.71865054]]\n",
"Błąd średniokwadratowy wynosi 39595039990.2324\n"
] ]
} }
], ],
@ -57,6 +58,8 @@
"\n", "\n",
"from sklearn.linear_model import LinearRegression # Model regresji liniowej z biblioteki scikit-learn\n", "from sklearn.linear_model import LinearRegression # Model regresji liniowej z biblioteki scikit-learn\n",
"\n", "\n",
"from sklearn.metrics import mean_squared_error\n",
"\n",
"\n", "\n",
"FEATURES = [\n", "FEATURES = [\n",
" 'Powierzchnia w m2',\n", " 'Powierzchnia w m2',\n",
@ -78,7 +81,6 @@
"\n", "\n",
"# Wczytanie danych\n", "# Wczytanie danych\n",
"data = pd.read_csv(dataset_filename, header=0, sep='\\t')\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 = data[FEATURES + ['cena']] # wybór cech\n",
"data = preprocess(data) # wstępne przetworzenie danych\n", "data = preprocess(data) # wstępne przetworzenie danych\n",
"\n", "\n",
@ -98,7 +100,12 @@
"x_test = pd.DataFrame(data_test[FEATURES])\n", "x_test = pd.DataFrame(data_test[FEATURES])\n",
"y_predicted = model.predict(x_test) # predykcja wyników na podstawie modelu\n", "y_predicted = model.predict(x_test) # predykcja wyników na podstawie modelu\n",
"\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", "name": "python",
"nbconvert_exporter": "python", "nbconvert_exporter": "python",
"pygments_lexer": "ipython3", "pygments_lexer": "ipython3",
"version": "3.8.3" "version": "3.7.6"
}, },
"livereveal": { "livereveal": {
"start_slideshow_at": "selected", "start_slideshow_at": "selected",