From 63fdac5217755b26a7671e6a7b0cf71e78271f6c Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E5=BC=A0=E6=9C=8B=E9=A3=9E?=
 <13190662+z1479344137@user.noreply.gitee.com>
Date: Sun, 16 Jul 2023 02:50:42 +0000
Subject: [PATCH] =?UTF-8?q?=E5=B9=B3=E6=97=B6=E4=BD=9C=E4=B8=9A?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Signed-off-by: 张朋飞 <13190662+z1479344137@user.noreply.gitee.com>
---
 .../第11组--张朋飞/案例代码/iris.py           | 25 +++++++++++++++++++
 1 file changed, 25 insertions(+)
 create mode 100644 车辆12分类数据集/第11组--张朋飞/案例代码/iris.py

diff --git a/车辆12分类数据集/第11组--张朋飞/案例代码/iris.py b/车辆12分类数据集/第11组--张朋飞/案例代码/iris.py
new file mode 100644
index 0000000..8385f24
--- /dev/null
+++ b/车辆12分类数据集/第11组--张朋飞/案例代码/iris.py
@@ -0,0 +1,25 @@
+from sklearn.datasets import load_iris
+from sklearn.model_selection import train_test_split
+from sklearn.neighbors import KNeighborsClassifier
+from sklearn.metrics import accuracy_score
+
+# 加载Iris数据集
+iris = load_iris()
+X = iris.data
+y = iris.target
+
+# 将数据集拆分为训练集和测试集
+X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
+
+# 分类器
+knn = KNeighborsClassifier(n_neighbors=3)
+
+# 在训练集上训练模型
+knn.fit(X_train, y_train)
+
+# 在测试集上进行预测
+y_pred = knn.predict(X_test)
+
+# 计算准确率
+accuracy = accuracy_score(y_test, y_pred)
+print('准确率：', accuracy)