Boosting for partially linear additive models
Additive models are widely applied in statistical learning. The partially linear additive model is a special form of additive models, which combines the strengths of linear and nonlinear models by allowing linear and nonlinear predictors to coexist. One of the most interesting questions associated w...
Main Author: | Tang, Xingyu |
---|---|
Other Authors: | Qin Yingli |
Format: | Thesis |
Language: | English |
Published: |
2016
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/69082 |
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