{
 "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": []
  }
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