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cross validation Code Example
classification cross validation 
from sklearn.model_selection import cross_val_predict
xgb=XGBClassifier(colsample_bytree=0.8, learning_rate=0.4, max_depth=4)
cvs=cross_val_score(xgb,x,y,scoring='accuracy',cv=10)
print('cross_val_scores=  ',cvs.mean())
y_pred=cross_val_predict(xgb,x,y,cv=10)
conf_mat=confusion_matrix(y_pred,y)
conf_mat
cross validation 
Cross-validation is a resampling procedure used to evaluate machine learning models on a limited data sample. The procedure has a single parameter called k that refers to the number of groups that a given data sample is to be split into. As such, the procedure is often called k-fold cross-validation.
cross validation error 
ModuleNotFoundError: No module named 'sklearn.cross_validation'



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