GridSearch & Kfold & cross validation

what’s cross validation?

Cross-validation is a technique that is used for the assessment of how the results of statistical analysis generalize to an independent data set. Cross-validation is largely used in settings where the target is prediction and it is necessary to estimate the accuracy of the performance of a predictive model. The prime reason for the use of cross-validation rather than conventional validation is that there is not enough data available for partitioning them into separate training and test sets (as in conventional validation). This results in a loss of testing and modeling capability.

Cross-validation is also known as rotation estimation.

summary of cross validation

• generate a data set based on statistical analysis
• cross-validation for evaluation the model effectively.
• not enough data

what’s the grid search?

Grid Search for Parameter Selection.

kfold?

kfold is the method to split the data into k folds.

what’s the ro