Why Shap is better than feature importance?

Why Shap is better than feature importance?

SHAP feature importance is an alternative to permutation feature importance. There is a big difference between both importance measures: Permutation feature importance is based on the decrease in model performance. SHAP is based on magnitude of feature attributions.

How do you summarize Shap values?

How to interpret the shap summary plot?

1. 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.
2. On the x-axis is the SHAP value.
3. Gradient color indicates the original value for that variable.
4. Each point represents a row from the original dataset.

What do you need to know about Shap values?

What Shapley does is quantifying the contribution that each player brings to the game. What SHAP does is quantifying the contribution that each feature brings to the prediction made by the model. It is important to stress that what we called a “game” concerns a single observation. One game: one observation.

Why is Shap feature importance with feature engineering?

Because the aim of the kernel is to showcase model importance output, basis for feature engineering is taken from a kernel, which scores well on LB. Data processing & feature engineering taken from: https://www.kaggle.com/qqgeogor/eda-script-67.

How are Shap values used to analyze model interpretability?

SHAP values provide a way to compare the feature importance at a global level. You can also change the dataset from global to a subset dataset of interest. 1. Computation time: Number of possible combinations of the features exponentially increases as more number of features are added.

Why are Shap values called Shapley additive explanations?

This is a fundamental characteristic of SHAP values: summing the SHAP values of each feature of a given observation yields the difference between the prediction of the model and the null model (or its logistic function, as we have seen here ). This is actually the reason for their name: SHapley Additive exPlanations.