I have watched the video of the resampling about Training data, testing data, cross-validation and Validation test approach. And also learned about bootstrapping.
Cross-validation, validation set and bootstrapping come under resampling methods. Resampling is a process in which it allows us to repeatedly draw samples from a set of observations from an existing data set and create a new data set from it. According to statistician Jim Frost “Bootstrapping is a statistical procedure that resamples a single data set to create many simulated samples. This process allows for the calculation of standard errors, confidence intervals, and hypothesis testing”. For Validation set approach, we divide the data into training set and testing set. We can say that it is the method which can estimate the error rate by taking out a subset from a known set. It is the testing set. The remaining set can be called as training set. And when a model is made using the training set, we can apply it to the testing set to calculate the error rate.