Influence of feature scaling on convergence of gradient iterative algorithm

Feature scaling is a method to unify self-variables or feature ranges in data. In data processing, it is usually used in data pre-processing. Because in the original data, the range of variables is very different. Feature scaling is a necessary step in the calculation of stochastic gradient descent....

Full description

Bibliographic Details

Published in:	Journal of physics. Conference series Vol. 1213; no. 3; pp. 32021 - 32025
Main Author:	Wan, Xing
Format:	Journal Article
Language:	English
Published:	Bristol IOP Publishing 01.06.2019
Subjects:	Convergence Data processing Iterative algorithms Iterative methods Scaling
ISSN:	1742-6588, 1742-6596
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!