机器学习(五)
Explainable AI
Interpretable v.s. Powerful
- • Are there some models interpretable and powerful at the same time? • How about decision tree? (A tree can still be terrible! We use a forest!)
Goal of Explainable ML
This is a “cat”.
- Local Explanation —— What does a “cat” look like?
- Global Explanation—— Why do you think this image is a cat?
Local Explanation: Explain the Decision
Which component is critical?——Removing or modifying the components Important component • Large decision change 没它不行(用灰色方块遮住 在不同位置)
How a network processes the input data?
visualization
probing
GLOBAL EXPLANATION: EXPLAIN THE WHOLE MODEL
Domain Adaptation
Domain shift: Training and testing data have different distributions
Little but labeled
Large amount of unlabeled data
让source()labeled和target(unlabeled)分不出差异
可能变成只是为了分开而分开 但分类不正确
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