<?xml version="1.0" encoding="UTF-8"?>
<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:title>Gradient Boosting</dc:title>
  <dc:title>R package bst version 0.3-24</dc:title>
  <dc:subject>CRAN Task View: MachineLearning (https://CRAN.R-project.org/view=MachineLearning)</dc:subject>
  <dc:description>Functional gradient descent algorithm for a variety of convex and non-convex loss functions, for both classical and robust regression and classification problems. See Wang (2011) &lt;doi:10.2202/1557-4679.1304&gt;, Wang (2012) &lt;doi:10.3414/ME11-02-0020&gt;, Wang (2018) &lt;doi:10.1080/10618600.2018.1424635&gt;, Wang (2018) &lt;doi:10.1214/18-EJS1404&gt;.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Imports: rpart, methods, foreach, doParallel, gbm</dc:relation>
  <dc:relation>Suggests: hdi, pROC, R.rsp, knitr, gdata</dc:relation>
  <dc:creator>Zhu Wang &lt;zwang145@uthsc.edu&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Zhu Wang [aut, cre] (ORCID: &lt;https://orcid.org/0000-0002-0773-0052&gt;),
  Torsten Hothorn [ctb]</dc:contributor>
  <dc:rights>GPL (&gt;= 2)</dc:rights>
  <dc:date>2023-01-06</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=bst</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.bst</dc:identifier>
</oai_dc:dc>