# 封装函数来进行knn试探性运算 def knn_score(k,X,y): # 构造算法对象 knn = KNeighborsClassifier(n_neighbors = k) scores = [] train_scores = [] for i in range(100): # 拆分 X_train,X_test,y_train,y_test = train_test_split(X,y,test_size=0.2,random_state=1) # 训练 knn.fit(X_train,y_train) # 评价模型 scores.append(knn.score(X_test,y_test)) # 经验评分 train_scores.append(knn.score(X_train,y_train)) return np.array(scores).mean(),np.array(train_scores).mean() # 调参 result_dict = {} k_list = [1,3,5,7,9,11] for k in k_list: score,train_score = knn_score(k,X,y) result_dict[k] = [score,train_score]利用这段代码调用tkinter库实现界面

可以使用`tkinter`库来创建一个窗口界面，然后在界面上添加按钮，当按钮被点击时，调用`knn_score()`函数进行试探性运算并将结果显示在界面上。

以下是一个简单的示例代码：

import tkinter as tk
from sklearn.neighbors import KNeighborsClassifier
from sklearn.model_selection import train_test_split
import numpy as np

def knn_score(k,X,y):
    # 构造算法对象
    knn = KNeighborsClassifier(n_neighbors = k)
    scores = []
    train_scores = []
    for i in range(100):
        # 拆分
        X_train,X_test,y_train,y_test = train_test_split(X,y,test_size=0.2,random_state=1)
        # 训练
        knn.fit(X_train,y_train)
        # 评价模型
        scores.append(knn.score(X_test,y_test))
        # 经验评分
        train_scores.append(knn.score(X_train,y_train))
    return np.array(scores).mean(),np.array(train_scores).mean()

# 创建窗口
root = tk.Tk()
root.title("KNN试探性运算")

# 添加标签
label1 = tk.Label(root, text="KNN试探性运算", font=("Arial", 16))
label1.pack()

# 添加按钮
button1 = tk.Button(root, text="运算", font=("Arial", 12))
button1.pack()

# 添加文本框
text1 = tk.Text(root, width=50, height=10)
text1.pack()

# 绑定按钮事件
def button_click():
    X = # 定义特征矩阵
    y = # 定义目标变量
    result_dict = {}
    k_list = [1,3,5,7,9,11]
    for k in k_list:
        score,train_score = knn_score(k,X,y)
        result_dict[k] = [score,train_score]
    # 将结果显示在文本框中
    text1.delete(1.0, tk.END)
    text1.insert(tk.END, str(result_dict))

button1.config(command=button_click)

# 运行窗口
root.mainloop()

注意：此示例代码中的`X`和`y`需要根据实际情况进行定义。