A Provably Accurate Randomized Sampling Algorithm for Logistic Regression

In statistics and machine learning, logistic regression is a widely-used supervised learning technique primarily employed for binary classification tasks. When the number of observations greatly exceeds the number of predictor variables, we present a simple, randomized sampling-based algorithm for l...

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Bibliographic Details

Published in:	arXiv.org
Main Authors:	Chowdhury, Agniva, Ramuhalli, Pradeep
Format:	Paper
Language:	English
Published:	Ithaca Cornell University Library, arXiv.org 31.03.2024
Subjects:	Algorithms Approximation Empirical analysis Linear algebra Machine learning Multiplication Regression Regression analysis Sampling Supervised learning
ISSN:	2331-8422
Online Access:	Get full text
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