【 biased regression methods to reduce variance---通过偏回归来减小方差】
https://onlinecourses.science.psu.edu/stat857/node/137
- Introducing biased regression methods to reduce variance
- Implementation of Ridge and Lasso regression
https://onlinecourses.science.psu.edu/stat857/node/155
【无惩罚，导致预测结果空间过大而无实用价值】
【fitting the full model without penalization will result in large prediction intervals】
Motivation: too many predictors
It is not unusual to see the number of input variables greatly exceed the number of observations, e.g. micro-array data analysis, environmental pollution studies.
With many predictors, fitting the full model without penalization will result in large prediction intervals, and LS regression estimator may not uniquely exist.
https://gerardnico.com/wiki/data_mining/lasso
