Visualizing SHAP Values with SHAP Explainer

This function uses the Explainer class from the SHAP library and the force_plot method to visualize the SHAP values for a single sample in a dataset. It takes an explainer, a dataset, and a list of feature names as input, and outputs an interactive SHAP value visualization chart.

Technology Stack : SHAP, Numpy, Pandas

Code Type : Custom function

Code Difficulty : Intermediate

                
                    
import numpy as np
import pandas as pd
import shap

def visualize_explanation(explainer, data, feature_names):
    """
    Visualize the SHAP values for a given explainer and data.
    
    Args:
    explainer (shap.Explainer): The SHAP explainer to use.
    data (pd.DataFrame): The input data for which to visualize the SHAP values.
    feature_names (list): The names of the features in the data.
    
    Returns:
    None
    """
    shap.initjs()
    shap.force_plot(explainer.expected_value, explainer.shap_values(data.iloc[0]), feature_names)