Machine Learning Interpretability
through Contribution-Value Plots
Dennis Collaris, Jarke J. van Wijk
Eindhoven University of Technology
International Symposium on Visual Communication and Interaction (VINCI 2020)
Data
Black
Box
Subject
80% risk
Why?
ML is often applied as a black box.
How?
Pre-existing techniques as elementary building blocks.
Prediction (ŷ)
x
ŷ
How?
Pre-existing techniques as elementary building blocks.
[1] Friedman, J. H. "Greedy function approximation: a gradient boosting machine.", 2001.
Prediction (ŷ)
Local PDP [1]
Sensitivity
analysis
x
ŷ
How?
Pre-existing techniques as elementary building blocks.
Prediction (ŷ)
Sensitivity
analysis
x
ŷ
[2] Goldstein, A., et al. "Peeking inside the black box: Visualizing statistical learning with plots of individual conditional expectation.", 2015.
Local PDP [1]
ICE plot [2]
Repeat
x
ŷ
How?
Pre-existing techniques as elementary building blocks.
[4] Lundberg, S. M., et. al.. "A unified approach to interpreting model predictions.". 2017.
Feature 1
Feature 2
Feature 3
Feature 4
Feature 5
[3] Ribeiro, M. T., et. al. ""Why should i trust you?" Explaining the predictions of any classifier.", 2016.
How?
Pre-existing techniques as elementary building blocks.
Prediction (ŷ)
Sensitivity
analysis
x
ŷ
Local PDP [1]
ICE plot [2]
Repeat
β
How?
Pre-existing techniques as elementary building blocks.
Prediction (ŷ)
Local PDP
ICE plot
Contribution (β)
Sensitivity
analysis
Repeat
x
ŷ
β
x
β
How?
Pre-existing techniques as elementary building blocks.
Prediction (ŷ)
Local PDP
ICE plot
Contribution (β)
LCV plot
Sensitivity
analysis
Sensitivity
analysis
Repeat
x
ŷ
β
x
β
How?
Pre-existing techniques as elementary building blocks.
Prediction (ŷ)
Local PDP
ICE plot
Contribution (β)
LCV plot
GCV plot
Sensitivity
analysis
Sensitivity
analysis
Repeat
Repeat
x
ŷ
β
x
β
Contribution-Value plots
Wine acidity (pH)
x
β
Contribution-Value plots
An exemplary data model exploration
Data
- 998 red wines
- 11 features
Model
- Random Forest (100 trees)
- Predict quality: 👍 / 👎
Contribution-Value plots
An exemplary data model exploration
x
β
x
β
Contribution-Value plots
An exemplary data model exploration
Wine acidity (pH)
x
β
x
ŷ
Contribution-Value plots
An exemplary data model exploration
??
Contribution-Value plots
Line fading . .
x
β
Contribution-Value plots
Conclusion
Check out the website
explaining.ml/cvplots
VINCI 2020
By iamdecode
