Contents
Why should I trust you explaining the predictions?
Such understanding also provides insights into the model, which can be used to transform an untrustworthy model or prediction into a trustworthy one. …
How do you interpret Shap value?
How to interpret the shap summary plot?
- The y-axis indicates the variable name, in order of importance from top to bottom. The value next to them is the mean SHAP value.
- On the x-axis is the SHAP value.
- Gradient color indicates the original value for that variable.
- Each point represents a row from the original dataset.
How do you explain Shap value?
SHAP values interpret the impact of having a certain value for a given feature in comparison to the prediction we’d make if that feature took some baseline value. An example is helpful, and we’ll continue the soccer/football example from the permutation importance and partial dependence plots lessons.
What does content agnostic mean?
As the definition of what consitutes a website continues to evolve, design will continue to function as content, and content will continue to perform as a design solution. Far from being decoration, a content agnostic approach forces us to produce a robust design solution that doesn’t impose itself on future content.
Which is better Shap or lime for local estimation?
SHAP values come with the black box local estimation advantages of LIME, but also come with theoretical guarantees about consistency and local accuracy from game theory (attributes from other methods we unified) I am having some trouble understanding what this ‘ theoretical guarantees about consistency and local accuracy from game theory ‘ is.
What’s the difference between Shapley and lime predictions?
LIME creates a surrogate model locally around the unit who’s prediction you wish to understand. Thus it is inherently local. Shapely values ‘decompose’ the final prediction into the contribution of each attribute – this is what some mean by ‘consistent’ (the values add up to the actual prediction of the true model,…
How are shapely values different from lime values?
Shapely values actually tell you, in an additive way, how you got your score, but there is some choice about the ‘starting point’ (i.e. the decision about omitted attributes). LIME simply tells you, in a local sense, what is the most important attribute around the data point of interest.
How is lime an example of a surrogate model?
LIME creates a surrogate model locally around the unit whose prediction you wish to understand. Thus it is inherently local.