The Role of Resampling Techniques in Data Science - KDnuggets

When working with models, you need to remember that different algorithms have different learning patterns when taking in data. It is a form of intuitive learning, to help the model learn the patterns in the given dataset, known as training the model. The model will then be tested on the testing dataset, a dataset the model has not seen before. You want to achieve an optimum performance level where the model can produce accurate outputs on both the training and testing dataset. You may have also heard of the validation set.