Feature selection is a critical step in data preprocessing, particularly in the field of cancer research. It involves selecting a subset of relevant features (variables, predictors) for use in model construction. The goal is to improve the performance of the model by eliminating irrelevant or redundant data, which can otherwise lead to overfitting or reduced accuracy.
