喜欢程度预测

import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
from sklearn.neighbors import KNeighborsClassifier
df=pd.read_csv("datatest.csv",names=["出行","游戏时间","冰淇淋","配对结果"])
print(df)
feature=df.iloc[:,0:3]
print(feature)
target=df.iloc[:,-1]
print(target)
x_train,x_test,y_train,y_test=train_test_split(feature,target,test_size=0.2,random_state=2000)
print(x_train.shape,x_test.shape)
from sklearn.preprocessing import StandardScaler
ss=StandardScaler()
x_train=ss.fit_transform(x_train)
print(x_train)
knn=KNeighborsClassifier(n_neighbors=4)
knn.fit(x_train,y_train)
x_test=ss.transform(x_test)
score=knn.score(x_test,y_test)
print(f"模型评分{score}")

x_test1=[[34621,4.122344,0.345678],[1,0,0]]
x_test1=ss.transform(x_test1)
y_predict=knn.predict(x_test1)
print(y_predict)