What Does Boosting Mean?

The process of boosting involves improving the power of a machine learning program by adding more complex or capable algorithms. This process can reduce both bias and variance in machine learning, which helps to create more effective results.


Techopedia Explains Boosting

Boosting processes are aimed at creating better overall machine learning programs that can produce more refined results. One way to look at this concept is in the context of weak and strong learning – where data scientists posit that a weak learner can be turned into a strong learner with either iteration or ensemble learning, or some other kind of technique. For example, stringing together several weaker algorithms can result in a stronger result.

Specific algorithms like AdaBoost or adaptive boosting use items like decision trees to creatively cobble together a stronger learning paradigm. That is the idea behind boosting, and it is something that is being used commonly in the evolution of machine learning technology.


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Margaret Rouse

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…