Using DALEX To Explain Black-Box Models

Przemyslaw Biecek explains that there’s more than LIME for explaining black-box models:

I’ve heard about a number of consulting companies, that decided to use simple linear model instead of a black box model with higher performance, because ,,client wants to understand factors that drive the prediction’’.
And usually the discussion goes as following: ,,We have tried LIME for our black-box model, it is great, but it is not working in our case’’, ,,Have you tried other explainers?’’, ,,What other explainers’’?

So here you have a map of different visual explanations for black-box models.

Check out DALEX, which includes a Jupyter notebook example.  H/T R-Bloggers

Related Posts

Using ggpairs To Find Correlations Between Variables In R

Akshay Mahale shows how to use the ggpairs function in R to see the correlation between different pairs of variables: From the above matrix for iris we can deduce the following insights: Correlation between Sepal.Length and Petal.Length is strong and dense. Sepal.Length and Sepal.Width seems to show very little correlation as datapoints are spreaded through out the plot area. Petal.Length and Petal.Width also shows strong correlation. Note: The […]

Read More

Testing Spatial Equilibrium Concepts With tidycensus

Ignacio Sarmiento Barbieri walks us through the concept of spatial equilibrium and tests using data from the tidycensus package: Let’s take the model to the data and reproduce figures 2.1. and 2.2 of “Cities, Agglomeration, and Spatial Equilibrium”. The focus are two cities, Chicago and Boston. These cities are chosen because both differ in how easy […]

Read More

Categories

June 2018
MTWTFSS
« May Jul »
 123
45678910
11121314151617
18192021222324
252627282930