Shed Light on Black Box Machine Learning Models
DEPRECATED
Create or Update a flashlight
Check functions for flashlight Classes
Variable Contribution Breakdown for Single Observation
Check flashlight
Combine Objects
Combination of Response, Predicted, Partial Dependence, and ALE profil...
Global Surrogate Tree
Individual Conditional Expectation (ICE)
Permutation Variable Importance
Interaction Strength
Model Performance of Flashlight
Partial Dependence and other Profiles
2D Partial Dependence and other 2D Profiles
DEPRECATED
Scatter Plot Data
Most Important Variables.
Create or Update a multiflashlight
DEPRECATED
Visualize Variable Contribution Breakdown for Single Observation
Visualize Multiple Types of Profiles Together
Plot Global Surrogate Trees
Visualize ICE profiles
Visualize Variable Importance
Visualize Model Performance
Visualize Profiles, e.g. Partial Dependence
Visualize 2D-Profiles, e.g., of Partial Dependence
Scatter Plot
Predictions for flashlight
Predictions for multiflashlight
Prints a flashlight
Prints light Object
Prints a multiflashlight
Residuals for flashlight
Residuals for multiflashlight
Response of multi/-flashlight
Shed light on black box machine learning models by the help of model performance, variable importance, global surrogate models, ICE profiles, partial dependence (Friedman J. H. (2001) <doi:10.1214/aos/1013203451>), accumulated local effects (Apley D. W. (2016) <doi:10.48550/arXiv.1612.08468>), further effects plots, interaction strength, and variable contribution breakdown (Gosiewska and Biecek (2019) <doi:10.48550/arXiv.1903.11420>). All tools are implemented to work with case weights and allow for stratified analysis. Furthermore, multiple flashlights can be combined and analyzed together.