When a Constant Classifier is as Good as Any Linear Classifier
type: Item
instance of: scholarly article
title: When a Constant Classifier is as Good as Any Linear Classifier
zbMATH Open document ID: 1238.62074
DOI: 10.1080/03610926.2010.498650
author: Steven P. Ellis
publication date: 2012-06-08T00:00:00Z
Mathematics Subject Classification ID: 62H30
Mathematics Subject Classification ID: 68T99
Mathematics Subject Classification ID: 68U20
zbMATH DE Number: 6044194
zbMATH Keywords: classification
zbMATH Keywords: logistic regression
zbMATH Keywords: misclassification rate
describes a project that uses: ElemStatLearn
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1080/03610926.2010.498650
OpenAlex ID: W1992258790
cites work: Q3997739
cites work: The hardness of approximate optima in lattices, codes, and systems of linear equations
cites work: Geometrical and Statistical Properties of Systems of Linear Inequalities with Applications in Pattern Recognition
cites work: The elements of statistical learning. Data mining, inference, and prediction
cites work: Linear Statistical Inference and its Applications
cites work: Q4261789
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published in: Communications in Statistics. Theory and Methods
description: scientific article; zbMATH DE number 6044194