Misconception 4: Explainable #machinelearning is just models of models.
I do like surrogate models. They have several important uses. However, I also REALLY like tools that explain models directly, including:
- ALE: https://lnkd.in/e3mz23V
- ICE: https://lnkd.in/eaQxk_Q
- Friedman's H-stat: https://lnkd.in/emwNcdy
- Partial dependence: https://lnkd.in/ejnkFYN, Section 10.13.2
- Shapley explanations: https://lnkd.in/ewsMxbU
(What did I miss? Any others?)
Moreover, surrogate models & direct explanatory techniques work very well together! See pic below.
Misconception 3: https://lnkd.in/eM3hVyW
Read more/contribute: https://lnkd.in/e8_hciE
#ai #datascience #deeplearning #aiforall #artificialintelligence #datascience #ml #python
✴️ @AI_Python_EN
I do like surrogate models. They have several important uses. However, I also REALLY like tools that explain models directly, including:
- ALE: https://lnkd.in/e3mz23V
- ICE: https://lnkd.in/eaQxk_Q
- Friedman's H-stat: https://lnkd.in/emwNcdy
- Partial dependence: https://lnkd.in/ejnkFYN, Section 10.13.2
- Shapley explanations: https://lnkd.in/ewsMxbU
(What did I miss? Any others?)
Moreover, surrogate models & direct explanatory techniques work very well together! See pic below.
Misconception 3: https://lnkd.in/eM3hVyW
Read more/contribute: https://lnkd.in/e8_hciE
#ai #datascience #deeplearning #aiforall #artificialintelligence #datascience #ml #python
✴️ @AI_Python_EN