如何使用 KNN 模型生成多个预测输出?

How to Generate Multiple Predictions Output with KNN Model?

我正在使用 predict() 函数从 KNN 模型生成预测,而不是只有一个预测,在这种情况下是 [10],我想要最有可能的 类。

可能吗?

这是我的代码:

import pandas as pd
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsClassifier
from sklearn.metrics import accuracy_score


df = pd.read_excel("Test.xlsx")
X = df.iloc[:,:4]
y = np.array(df['Target']) 

# split into train and test
X_train, 
X_test, 
y_train, 
y_test = train_test_split(X, y, test_size=0.33, random_state=42)

# instantiate learning model (k = 7)
knn = KNeighborsClassifier(n_neighbors=7)

# fitting the model
knn.fit(X_train, y_train)

# predict the response
pred = knn.predict(X_test)

#Predict Output
pred= knn.predict([[2,3,90,600]]) 


**Output:**
**[10]**

您可以添加如下内容:

print(knn.predict_proba(X_test)

这将打印出如下内容: [x1. x2. x3. x4.],显示每个 class 的概率或置信度。此方法将为测试集中的每个项目打印出该格式。