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Introduction to Regularization
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Do curso por University of Illinois at Urbana-Champaign
Data Analytics Foundations for Accountancy II
University of Illinois at Urbana-Champaign
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Module 4: Overfitting & Regularization
This module introduces the concept of regularization, problems it can cause in machine learning analyses, and techniques to overcome it. First, the basic concept of overfitting is presented along with ways to identify its occurrence. Next, the technique of cross-validation is introduced, which can mitigate the likelihood that overfitting can occur. Next, the use of cross-validation to identify the optimal parameters for a machine learning algorithm trained on a given data set is presented. Finally, the concept of regularization, where an additional penalty term is applied when determining the best machine learning model parameters, is introduced and demonstrated for different regression and classification algorithms.
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Robert BrunnerProfessor
Accountancy
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