feature selection

While it’s great to have a lot of data, not every variable (aka feature) in your dataset will be equally informative in a predictive model. Typically you want to build models using the most valuable features, and omit those that offer less information for the predictions or that are redundant. Feature selection is the process of determining the value of each variable to the model and deciding which variables to keep in the model.