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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Vydané v:	arXiv.org
Hlavní autori:	Chowdhury, Agniva, Ramuhalli, Pradeep
Médium:	Paper
Jazyk:	English
Vydavateľské údaje:	Ithaca Cornell University Library, arXiv.org 31.03.2024
Predmet:	Algorithms Approximation Empirical analysis Linear algebra Machine learning Multiplication Regression Regression analysis Sampling Supervised learning
ISSN:	2331-8422
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