Ensemble Learning

What Does Ensemble Learning Mean?

Ensemble learning is the use of algorithms and tools in machine learning and other disciplines, to form a collaborative whole where multiple methods are more effective than a single learning method. Ensemble learning can be used in many different types of research, for flexibility and enhanced results.


Techopedia Explains Ensemble Learning

Many ensemble learning tools can be trained to produce various results. Individual algorithms may be stacked on top of each other, or rely on a “bucket of models” method of evaluating multiple methods for one system. In some cases, multiple data sets are aggregated and combined. For example, a geographic research program may use multiple methods to assess the prevalence of items in a geographic space. One of the issues with this type of research involves making sure that various models are independent, and that the combination of data is practical and works in a particular scenario.

Ensemble learning methods are included in different types of statistical software packages. Some experts describe ensemble learning as “crowdsourcing” of data aggregation.


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Margaret Rouse is an award-winning technical writer and teacher known for her ability to explain complex technical subjects to a non-technical, business audience. Over the past twenty years her explanations have appeared on TechTarget websites and she's been cited as an authority in articles by the New York Times, Time Magazine, USA Today, ZDNet, PC Magazine and Discovery Magazine.Margaret's idea of a fun day is helping IT and business professionals learn to speak each other’s highly specialized languages. If you have a suggestion for a new definition or how to improve a technical explanation, please email Margaret or contact her…