Machine Learning Tutorial with Python | Selecting best model in scikit-learn using cross-validation
Hi guys…in this Practical Machine Learning Tutorial with Python, I have talked about how you can select the best variables for model by using cross val score method of sklearn library. Cross val score helps identifying whether the model accuracy is increasing significantly or not by adding a new variable. If it is not, then you can drop that variable otherwise add it.
Selecting the best model in scikit-learn using cross-validation
In this video, we’ll learn about K-fold cross-validation and how it can be used for selecting optimal tuning parameters, choosing between models, and selecting features. We’ll compare cross-validation with the train/test split procedure, and we’ll also discuss some variations of cross-validation that can result in more accurate estimates of model performance.