Why are Filter Methods Important in Cancer Research?
Cancer datasets often contain thousands of features, but only a subset of these may be relevant for diagnosis, prognosis, or treatment. Filter methods help in reducing the dimensionality of the data, making models more interpretable and reducing the risk of overfitting. This is critical for improving the accuracy of predictive models and discovering potential biomarkers.
