Why is Lasso Regression Important in Cancer Research?
Cancer research often involves high-dimensional datasets, such as gene expression profiles, where the number of predictors (genes) can far exceed the number of samples. In such scenarios, traditional regression methods can lead to overfitting. Lasso regression mitigates this by selecting a subset of relevant predictors, making the models more robust and interpretable. This is particularly useful for identifying potential biomarkers for cancer diagnosis, prognosis, and treatment response.
