#!/usr/bin/env python
# coding: utf-8

# # 5.1.4 반복 교차 검증

# *아래 링크를 통해 이 노트북을 주피터 노트북 뷰어(nbviewer.org)로 보거나 구글 코랩(colab.research.google.com)에서 실행할 수 있습니다.*
# 
# <table class="tfo-notebook-buttons" align="left">
#   <td>
#     <a target="_blank" href="https://nbviewer.org/github/rickiepark/intro_ml_with_python_2nd_revised/blob/main/05.1.4-RepeatedKFold.ipynb"><img src="https://jupyter.org/assets/share.png" width="60" />주피터 노트북 뷰어로 보기</a>
#   </td>
#   <td>
#     <a target="_blank" href="https://colab.research.google.com/github/rickiepark/intro_ml_with_python_2nd_revised/blob/main/05.1.4-RepeatedKFold.ipynb"><img src="https://www.tensorflow.org/images/colab_logo_32px.png" />구글 코랩(Colab)에서 실행하기</a>
#   </td>
# </table>

# In[1]:


from sklearn.model_selection import cross_val_score, KFold, StratifiedKFold
from sklearn.datasets import load_iris
from sklearn.linear_model import LogisticRegression

iris = load_iris()
logreg = LogisticRegression(max_iter=1000)


# In[2]:


from sklearn.model_selection import RepeatedStratifiedKFold

rskfold = RepeatedStratifiedKFold(random_state=42)
scores = cross_val_score(logreg, iris.data, iris.target, cv=rskfold)

print("교차 검증 점수:\n", scores)
print("교차 검증 평균 점수: {:.3f}".format(scores.mean()))