Random Eli5 Function for Explaining SKLearn Models

This code defines a function named random_eli5_function that randomly selects a function from the Eli5 library to explain a randomly generated RandomForestClassifier model. First, it randomly selects a function from the Eli5 library, then creates a random classification dataset and a RandomForestClassifier model. Next, it uses the selected function to explain the model.

Technology Stack : Eli5, SKLearn

Code Type : The type of code

Code Difficulty : Intermediate

                
                    
import random
import eli5
from eli5.sklearn import PermutationImportance

def random_eli5_function():
    # Randomly select an Eli5 function and use it
    selected_function = random.choice([
        eli5.explain_weights,
        eli5.show_weights,
        eli5.explain,
        eli5.show_explanation
    ])
    
    # Randomly select a SKLearn model to explain
    from sklearn.datasets import make_classification
    from sklearn.ensemble import RandomForestClassifier
    X, y = make_classification(n_samples=100, n_features=20, random_state=42)
    model = RandomForestClassifier(n_estimators=10, random_state=42)
    model.fit(X, y)
    
    # Use the selected function to explain the model
    explanation = selected_function(model, X)
    
    return explanation