BigML acquired the best-of-class Association Discovery technology Magnum Opus from Dr. Geoff Webb of Melbourne’s Monash University in July 2015. Dr. Webb invented the Averaged One-Dependence Estimators Machine Learning algorithm and its generalization the Averaged N-Dependence Estimators.
This proprietary algorithm embodies the state-of-the-art in the field of Association Discovery and complements other statistical data mining techniques since it:
- Avoids the problems due to model selection as association mining can find all local models rather than a single global model.
- Scales very effectively to high-dimensional data as it can process thousands of variables.
- Concentrates on discovering relationships between values of variables rather than just variables.
- Is able to measure the meaningfulness of associations, so it focuses on finding valuable associations instead of minimizing the risk of making false discoveries.
In this blog post you will find the main differences and advantages of the BigML unique and differentiated approach to Association Discovery.