Loading subject…
Embedded method
A feature selection strategy in which the selection happens inside the training process of a single model, so the model decides which features matter as it fits.
Feature selection
Feature selection is the process of identifying and retaining the most informative attributes of a data set while removing those that are redundant or irrelevant.
Filter method
A feature selection strategy that scores each feature on its own statistical relationship with the target variable, before any model is trained, and keeps the highest scoring features.
Wrapper method
A feature selection strategy that evaluates a subset of features by training a model on that subset and measuring the resulting performance, repeating the search until the best performing subset is found.