You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
76 lines
1.9 KiB
76 lines
1.9 KiB
{
|
|
"cells": [
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 2,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"数据集结构： (150, 4)\n",
|
|
"测试集大小： (30, 4)\n",
|
|
"真实结果： [2 1 0 2 0 2 0 1 1 1 2 1 1 1 1 0 1 1 0 0 2 1 0 0 2 0 0 1 1 0]\n",
|
|
"预测结果： [2 1 0 2 0 2 0 1 1 1 2 1 1 1 2 0 1 1 0 0 2 1 0 0 2 0 0 1 1 0]\n",
|
|
"预测精确率： 0.9666666666666667\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"from sklearn import datasets\n",
|
|
"from sklearn.neighbors import KNeighborsClassifier\n",
|
|
"from sklearn.model_selection import train_test_split\n",
|
|
"#导入鸢尾花数据并查看数据特征\n",
|
|
"iris = datasets.load_iris()\n",
|
|
"print('数据集结构：',iris.data.shape)\n",
|
|
"# 获取属性\n",
|
|
"iris_X = iris.data\n",
|
|
"# 获取类别\n",
|
|
"iris_y = iris.target\n",
|
|
"# 划分成测试集和训练集\n",
|
|
"iris_train_X,iris_test_X,iris_train_y,iris_test_y=train_test_split(iris_X,iris_y,test_size=0.2, random_state=0)\n",
|
|
"#分类器初始化\n",
|
|
"knn = KNeighborsClassifier()\n",
|
|
"#对训练集进行训练\n",
|
|
"knn.fit(iris_train_X, iris_train_y)\n",
|
|
"#对测试集数据的鸢尾花类型进行预测\n",
|
|
"predict_result = knn.predict(iris_test_X)\n",
|
|
"\n",
|
|
"#补充程序，显示下面的程序结果\n",
|
|
"\n",
|
|
"\n",
|
|
"\n",
|
|
"\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.6.5"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 2
|
|
}
|