Visualizing SHAP Values with SHAP Library

This function uses the SHAP library to visualize the SHAP values for a given model and data. It takes input features, target variable, model, and feature names as inputs and generates a visualization of the SHAP values.

Technology Stack : SHAP, Numpy

Code Type : The type of code

Code Difficulty : Intermediate

                
                    
import numpy as np
import shap

def visualize_shap_values(X, y, model, feature_names):
    """
    Visualize the SHAP values for a given model and data.

    Args:
        X (numpy.ndarray): Input features.
        y (numpy.ndarray): Target variable.
        model: Model object that supports predict method.
        feature_names (list): Names of the features.
    """
    explainer = shap.Explainer(model.predict, X)
    shap_values = explainer(X)
    
    shap.summary_plot(shap_values, X, feature_names=feature_names)

# Code Information