diff --git a/HW 5/Iris_knn_W2025_template.ipynb b/HW 5/Iris_knn_W2025_template.ipynb
index a443351..f67157d 100644
--- a/HW 5/Iris_knn_W2025_template.ipynb
+++ b/HW 5/Iris_knn_W2025_template.ipynb
@@ -40,7 +40,7 @@
},
{
"cell_type": "code",
- "execution_count": 11,
+ "execution_count": 49,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -49,134 +49,18 @@
"id": "DjCaxH3BKJ_O",
"outputId": "ab33e45d-d332-412e-db2a-88cc4c9528f4"
},
- "outputs": [
- {
- "data": {
- "text/html": [
- "
\n",
- "\n",
- "
\n",
- " \n",
- " \n",
- " | \n",
- " sepal length (cm) | \n",
- " sepal width (cm) | \n",
- " petal length (cm) | \n",
- " petal width (cm) | \n",
- "
\n",
- " \n",
- " \n",
- " \n",
- " | 0 | \n",
- " 5.1 | \n",
- " 3.5 | \n",
- " 1.4 | \n",
- " 0.2 | \n",
- "
\n",
- " \n",
- " | 1 | \n",
- " 4.9 | \n",
- " 3.0 | \n",
- " 1.4 | \n",
- " 0.2 | \n",
- "
\n",
- " \n",
- " | 2 | \n",
- " 4.7 | \n",
- " 3.2 | \n",
- " 1.3 | \n",
- " 0.2 | \n",
- "
\n",
- " \n",
- " | 3 | \n",
- " 4.6 | \n",
- " 3.1 | \n",
- " 1.5 | \n",
- " 0.2 | \n",
- "
\n",
- " \n",
- " | ... | \n",
- " ... | \n",
- " ... | \n",
- " ... | \n",
- " ... | \n",
- "
\n",
- " \n",
- " | 146 | \n",
- " 6.3 | \n",
- " 2.5 | \n",
- " 5.0 | \n",
- " 1.9 | \n",
- "
\n",
- " \n",
- " | 147 | \n",
- " 6.5 | \n",
- " 3.0 | \n",
- " 5.2 | \n",
- " 2.0 | \n",
- "
\n",
- " \n",
- " | 148 | \n",
- " 6.2 | \n",
- " 3.4 | \n",
- " 5.4 | \n",
- " 2.3 | \n",
- "
\n",
- " \n",
- " | 149 | \n",
- " 5.9 | \n",
- " 3.0 | \n",
- " 5.1 | \n",
- " 1.8 | \n",
- "
\n",
- " \n",
- "
\n",
- "
150 rows × 4 columns
\n",
- "
"
- ],
- "text/plain": [
- " sepal length (cm) sepal width (cm) petal length (cm) petal width (cm)\n",
- "0 5.1 3.5 1.4 0.2\n",
- "1 4.9 3.0 1.4 0.2\n",
- "2 4.7 3.2 1.3 0.2\n",
- "3 4.6 3.1 1.5 0.2\n",
- ".. ... ... ... ...\n",
- "146 6.3 2.5 5.0 1.9\n",
- "147 6.5 3.0 5.2 2.0\n",
- "148 6.2 3.4 5.4 2.3\n",
- "149 5.9 3.0 5.1 1.8\n",
- "\n",
- "[150 rows x 4 columns]"
- ]
- },
- "execution_count": 11,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"####################################\n",
- "from sklearn.datasets import load_iris\n",
+ "#from sklearn.datasets import load_iris\n",
"#data = load_iris()\n",
- "df = pd.DataFrame(data.data, columns=data.feature_names)\n",
- "df"
+ "#df = pd.DataFrame(data.data, columns=data.feature_names)\n",
+ "#df"
]
},
{
"cell_type": "code",
- "execution_count": 13,
+ "execution_count": 50,
"metadata": {
"id": "ANJhDRNPKPR5"
},
@@ -276,7 +160,7 @@
"4 5.0 3.6 1.4 0.2 setosa remove_me"
]
},
- "execution_count": 13,
+ "execution_count": 50,
"metadata": {},
"output_type": "execute_result"
}