LASS(Least Absolute Shrinkage and Selection Operator)是一种用于特征选择的方法,也称为Lasso回归。这种方法通过引入正则化项来约束回归系数绝对值的总和,从而在最小化预测误差的同时,对一些系数进行收缩和选择。Lasso回归可以用于特征选择,通过选择一些系数为零的特征来减少模型的复杂性,同时保留重要的特征。
1. Linear and Locally Smooth Approximation (LASS)
2. Least Absolute Shrinkage Selection Operator (LASSP)
3. Least Squares Smoothing (LASSO)
4. Least Squares Smoothing Splines (LASSS)
5. Least Absolute Deviations (LAD)
6. Least Absolute Deviation Classification (LAD-C)
7. Least Mean Squares (LMSM)
8. Least Mean Square Classification (LMSM-C)
9. Least Squares Classification (LSC)