Machine Learning : Cross Validation Technique

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Cross validation is one way to avoid over fitting of data in machine learning .
Cross validation works in such way :

1st Way : One Round Cross Validation :  in this data is divided into  50-50 portion ,one portion is for test set , one portion is validation of model that is prepared with the help of 50% of data .

Leave one out cross validation(LOOCV)  :

 In this ,we leave one data set for cross validation  and rest data set for use for training of model .

k-fold cross validation : In this k data set are used to trained  the model ,while k-1 are using for validate or test  the model .


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