The study of why these ensemble methods succeed is of fundamental importance. If we
understand precisely why, when, and how particular ensemble methods can be applied successfully,
we will have made progress toward a powerful new tool for machine learning: the
ability to automatically exploit the strengths and weaknesses of different learning systems.
The issue of diversity is therefore a topic of great draw and depth, offering wide-ranging
implications and a fascinating community of researchers to work within. To contribute
meaningful knowledge in such an interdisciplinary subject, a focal point for study within it
must be quickly identified