Least Mean Square Algorithm

What Does Least Mean Square Algorithm Mean?

The least mean square (LMS) algorithm is a type of filter used in machine learning that uses stochastic gradient descent in sophisticated ways – professionals describe it as an adaptive filter that helps to deal with signal processing in various ways.


Techopedia Explains Least Mean Square Algorithm

The least mean square algorithm uses a technique called “method of steepest descent” and continuously estimates results by updating filter weights. Through the principle of algorithm convergence, the least mean square algorithm provides particular learning curves useful in machine learning theory and implementation. Many of these ideas are part of dedicated work on refining machine learning models, matching inputs to outputs, making training and test processes more effective, and generally pursuing “convergence” where the iterative learning process resolves into a coherent final result instead of getting off track.


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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…