Ensemble machine learning combines the power of multiple machine learning approaches, working together to deliver models that are highly performant and highly accurate.Inside
Ensemble Methods for Machine Learning you will find:
- Methods for classification, regression, and recommendations
- Sophisticated off-the-shelf ensemble implementations
- Random forests, boosting, and gradient boosting
- Feature engineering and ensemble diversity
- Interpretability and explainability for ensemble methods
Ensemble machine learning trains a diverse group of machine learning models to work together, aggregating their output to deliver richer results than a single model. Now in
Ensemble Methods for Machine Learning you’ll discover core ensemble methods that have proven records in both data science competitions and real-world applications. Hands-on case studies show you how each algorithm works in production. By the t
