CatBoost Classification Model Accuracy Calculator

This function uses the CatBoost library to load a classification model, make predictions on the given data, and calculate the accuracy of the predictions.

Technology Stack : CatBoost, NumPy

Code Type : Machine learning classification function

Code Difficulty : Intermediate

                
                    
def random_catboost_classification(model_path, data, target_column):
    import catboost as cb
    import numpy as np

    # Load the CatBoost model from a file
    model = cb.CatBoostClassifier()
    model.load_model(model_path)

    # Make predictions using the loaded model
    predictions = model.predict(data)

    # Calculate the accuracy of the predictions
    accuracy = np.mean(predictions == data[target_column])

    return accuracy