Relaxed Adaptive Lasso for Classification on High-Dimensional Sparse Data with Multicollinearity
Relaxed Adaptive Lasso for Classification on High-Dimensional Sparse Data with Multicollinearity
High-dimensional sparse data with multicollinearity is frequently found in medical data. This problem can lead to poor predictive accuracy when applied to a new data set. The Least Absolute Shrinkage and Selection Operator (Lasso) is a popular machine-learning algorithm for variable selection and parameter estimation. Additionally, the adaptive Lasso method …