机器学习基石 - Noise and Error
机器学习基石上 (Machine Learning Foundations)—Mathematical Foundations
Hsuan-Tien Lin, 林轩田，副教授 (Associate Professor)，资讯工程学系 (Computer Science and Information Engineering)
Noise and Probabilistic Target
确定的改为概率，保证同一分布下
练习题
Error Measure
- out of sample
- pointwise
- classification
- 0/1 error often for classification; squared error often for regression
- extended VC theory/philosophy works for most and err
Algorithmic Error Measure
- err is application/user-dependent
- 学习流程图
Weighted Classification
- 不同的情形有不同的权重
- Weighted Pocket Algorithm