automlbench 0.1.1

A Python package for automated ML model benchmarking and comparison

AutoMLBench- Automated ML Model Benchmarking Library

Automlbench is a Python library for automated machine learning model benchmarking. It simplifies the process of comparing multiple machine learning models by providing utilities for data loading, preprocessing, model selection, hyperparameter tuning, evaluation, and visualization. The library is designed to streamline model experimentation and performance analysis, making it ideal for data scientists and machine learning practitioners.

🚀 Features

✅ Automated model benchmarking – Compare multiple models with minimal effort.
✅ Flexible preprocessing – Choose between automatic or manual feature engineering.
✅ Performance visualization – Generate insightful plots for model comparison.
✅ Customizable feature handling – Supports missing value imputation, scaling, and encoding.
✅ Multi-model training – Supports Random Forest, Gradient Boosting, XGBoost, LightGBM, CatBoost, and more.

Installation

pip install automlbench

Importing Automlbench

from automlbench import (
    load_data, preprocess_data, get_models, get_hyperparameter_grids,
    evaluate_model, plot_performance, tune_hyperparameters, 
    time_execution, log_message, suppress_warnings
)

Features

1. Load Data

df = load_data("dataset.csv")

2. Preprocess Data

X_train, X_test, y_train, y_test = preprocess_data(df, target_column="target")

3. Get Available Models

models = get_models()

4. Hyperparameter Grids

param_grids = get_hyperparameter_grids()

5. Evaluate Models

results = {name: evaluate_model(model, X_test, y_test) for name, model in trained_models.items()}

6. Hyperparameter Tuning

best_models = tune_hyperparameters(models, X_train, y_train, param_grids)

7. Plot Performance

plot_performance(results)

8. Suppress Warnings (Optional)

suppress_warnings(True)  # Set to False if you want to see warnings

Utilities

• time_execution(func): Measure execution time of a function.
• log_message(msg): Log messages for debugging.

License

This project is licensed under the MIT License.