如何使用 python 根据输入值划分数组

Question

假设 KNN 中的折叠值是 N，我们需要将数组分成 N 等份，对于折叠值的每次迭代，我们需要划分火车并以这种方式进行测试

example :
fold is 5
1. In First iteration It Consider last means 5th part as test data and rest train data
2. In Second iteration It Consider second last means 4th part as test data and rest train data
3. In third iteration It Consider third last means 3rd part as test data and rest train data
... so on
5. In  Firth iteration It Consider first means 1st part as test data and rest train data

我们如何在 Python 中实现这一点，请您解释一下。

Answer 1

我觉得你需要 KFold https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.KFold.html

# you can declare number of splits here
kfold = model_selection.KFold(n_splits=5, random_state=42)
# your model goes here. 
model = NearestNeighbors(n_neighbors=2, algorithm='ball_tree')
# this will fit your model 5 times and use 1/5 as test data and 4/5 as training data
results = model_selection.cross_val_score(model, X_train,  y_train, cv=kfold)

如何使用 python 根据输入值划分数组

How to divide the array based on Input value using python

python

machine-learning

knn

data-science