from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsClassifier
import numpy as np
import pandas as pd
df = pd.read_csv('social.csv', names=["flight", "icecream", "games", "type"])
features = df.drop(columns="type")
targets = df["type"]
# 数据集 测试集拆分
X_train, X_test, y_train, y_test = train_test_split(features, targets, test_size=0.25)
knn = KNeighborsClassifier()
knn.fit(X_train, y_train)
ret = knn.score(X_test, y_test)
