Cross Validation For Model Selection |K-Fold|Leave One Out CV | Data Science

Cross validations are useful way to evaluate models. The best fit model can be found out by cross validating and choosing the one that has least models. CV techniques are very useful in all data science projects. We would take K-fold & Leave one out cross validation to demonstrate the techniques.
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[@vishalaaa1]

Very good . These vides will be hit. Please make more videos and cover all real time practical's and make them one set. It will be hit.

[@AnalyticsUniversity]

Thank you!

[@maheshmanchineni6236]

Hi sir thanks for the video you explained it very clear but how would be our approach if we are having more than one predictor variables how do we write the final equation.

[@PSILoveMathProfessorSampson]

How do you do another iteration so you get different values. Like what if I wanted 10 sets of data