BLOG Q&A

Why would you use Regularization and what it is?

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Why would you use Regularization and what it is? In Machine Learning, very often the task is to fit a model to a set of training data and use the fitted model to make predictions or classify new (out of sample) data points. Sometimes model fits the training data very well but does not well …

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BLOG GLOSSARY

What is Regularization?

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Regularization in the field of machine learning is a process of introducing additional information in order to solve an ill-posed problem or to prevent overfitting. A theoretical justification for regularization is that it attempts to impose Occam’s razor on the solution, as depicted in the figure. From a Bayesian point of view, many regularization techniques …

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