Estimating classification error rate: repeated cross-validation, repeated hold-out and bootstrap
type: Item
instance of: scholarly article
title: Estimating classification error rate: repeated cross-validation, repeated hold-out and bootstrap
zbMATH Open document ID: 1453.62126
author: B. E. Eshmatov
published in: Computational Statistics and Data Analysis
publication date: 2010-04-01T00:00:00Z
Mathematics Subject Classification ID: 62-08
Mathematics Subject Classification ID: 62H30
zbMATH DE Number: 5689130
describes a project that uses: R
describes a project that uses: AdaBoost.MH
describes a project that uses: bootstrap
describes a project that uses: rpart
MaRDI profile type: Publication
full work available at URL: j.csda.2009.04.009
OpenAlex ID: W2073792037
cites work: Q3327527
cites work: A comparative study of ordinary cross-validation, v-fold cross-validation and the repeated learning-testing methods
cites work: Estimating the Error Rate of a Prediction Rule: Improvement on Cross-Validation
cites work: Improvements on Cross-Validation: The .632+ Bootstrap Method
cites work: A decision-theoretic generalization of on-line learning and an application to boosting
cites work: ASSESSING ERROR RATE ESTIMATORS: THE LEAVE‐ONE‐OUT METHOD RECONSIDERED
cites work: Ten More Years of Error Rate Research
cites work: A Comparison of Nonparametric Error Rate Estimation Methods in Classification Problems
DOI: 10.1016/J.CSDA.2009.04.009
description: scientific article; zbMATH DE number 5689130