Help Center/ FunctionGraph/ User Guide/ Configuring Functions/ Configuring Dependencies/ Public Dependency Demos/ sklearn
Updated on 2023-11-16 GMT+08:00
sklearn
Adding sklearn on Function Details Page
Figure 1 Adding sklearn
Importing sklearn to Code
# Import sklearn.
from sklearn import datasets
from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsClassifier
def handler (event, context):
iris=datasets.load_iris()
iris_X=iris.data
iris_y=iris.target
X_train,X_test,y_train,y_test=train_test_split(iris_X,iris_y,test_size=0.3)
knn=KNeighborsClassifier()
knn.fit(X_train,y_train)
print(knn.predict(X_test))
return y_test Parent topic: Public Dependency Demos
What is your overall rating for this page?
0
1
2
3
4
5
6
7
8
9
10
Very dissatisfiedVery satisfied
Thank you very much for your feedback. We will continue working to improve the documentation.
The system is busy. Please try again later.