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Bias/Variance in Neural Networks by dd is a document available to read on EtoBox.

What is Bias/Variance in Neural Networks about?

This document provides an introduction to the bias/variance dilemma in neural networks and nonparametric inference. It discusses how neural networks can be viewed as performing nonlinear regression to fit training data. However, truly model-free ("tabula rasa") approaches suffer from high variance, requiring prohibitively large training sets. The bias/variance dilemma is that while incorrect models lead to high bias, model-free methods have high variance. The document argues that learning complex tasks is i

Author

dd

Language

EN