modeva.TestSuite.interpret_fi#
- TestSuite.interpret_fi(dataset: str = 'test')#
Calculate and visualize global feature importance for the model.
This function computes the importance of each feature in the model’s predictions and creates a horizontal bar plot visualization of the results.
- Parameters:
dataset ({"main", "train", "test"}, default="test") – The data set used for calculating the explanation results.
- Returns:
A container object with the following components:
key: “interpret_ei”
data: Name of the dataset used
model: Name of the model used
inputs: Input parameters
value: Dictionary containing:
”Name”: List of feature names
”Importance”: List of corresponding feature importance values
table: DataFrame containing feature names and importance values
options: Dictionary of visualizations configuration for a horizontal bar plot where x-axis is importance, and y-axis is the feature names. Run results.plot() to show this plot.
- Return type:
Examples
