24 research outputs found
Appendix D. Fitting boosted trees to data with multi-level errors.
Fitting boosted trees to data with multi-level errors
Appendix A. Simulations comparing aggregated boosted trees and boosted trees.
Simulations comparing aggregated boosted trees and boosted trees
Supplement 1. A library of S-Plus functions for tree analyses (including multivariate regression trees).
<h2>File List</h2><blockquote>
<p> Supplement 1, original
</p><p><a href="TREES.zip">TREES.ZIP</a></p>
<p>Supplement 1, revision 1 (22 March
2002)
</p><p><a href="TREES2.zip">TREES2.ZIP</a></p>
<p>Supplement 1, revision 2 (26 March
2002) </p>
<p><a href="TREES3.zip">TREES3.ZIP</a></p>
</blockquote><h2>Description</h2><p>S-Plus library (3.3 for Windows)
of tree routines including mulivariate trees and other ordination methods.</p>
<p>The program is menu-driven and includes
help and example files.</p
Appendix B. A classification example of boosting using fish scale data.
A classification example of boosting using fish scale data
Supplement 1. R software packages for boosted trees.
<h2>File List</h2><blockquote>
<p><a href="gbmplus_1.5-17.zip">gbmplus_1.5-17.zip</a></p>
<p>R package suitable for installation on Windows OS.</p>
<p><a href="gbmplus_1.5-17.tar.gz">gbmplus_1.5-17.tar.gz</a></p>
<p>R package sources suitable for installation on all supported OS(Linux/Unix/Windows).</p>
<p><a href="softcorals.csv">softcorals.csv</a></p>
<p>Data for soft coral analysis in paper. Variable names are in row 1 and details of all variables are supplied in the paper.</p>
<p><a href="barramundi.csv">barramundi.csv</a></p>
<p>Data for barramundi analysis in Appendix One. Variable names are in row 1 and details of all variables are supplied in Appendix One.</p>
</blockquote><h2>Description</h2><blockquote>
<p>Package: gbmplus</p>
<p>Version: 1.5-17</p>
<p>Date: 2006-07-01</p>
<p>Title: Generalized Boosted Regression Models</p>
<p>Author: Greg Ridgeway Modifications of package gbm by Glenn De'ath </p>
<p>Maintainer: Glenn De'ath </p>
<p>Depends: R (>= 2.1.0), lattice</p>
<p>Description: This package implements extensions to Freund and Schapire's AdaBoost algorithm and J. Friedman's gradient boosting machine. Includes regression methods for least squares, absolute loss, logistic, Poisson, Cox proportional hazards partial likelihood, and AdaBoost exponential loss. Includes aggregated boosting (GD).</p>
<p>License: GPL (version 2 or newer)</p>
<p>URL: http://www.i-pensieri.com/gregr/gbm.shtml</p>
<p>Packaged: Tue Jul 4 11:34:54 2006; Glenn</p>
<p>The most flexible, accessible environment with access to tree and boosting software is the R software. R is a freely available GNU version of the S language, includes extensive statistical computing and graphics procedures, and runs on a wide variety of UNIX platforms, Windows and MacOS. R packages for fitting classification and regression trees include rpart, mvpart and tree. For boosting, the packages gbm and boost are available and gbmplus (a modified version of gbm) that implements aggregated boosting and is available from here or the author at <a href="mailto:[email protected]">[email protected]</a>. The R packages randomForest and ipred are available for random forests and bagging. Commercial software for trees, boosting and random forests is available from Salford Systems. </p>
<p>The package gbmplus is available from these Ecological Archives in zip format for Windows users and tar format for Linux users. </p>
</blockquote
Appendix A. A table showing simulation results to determine analysis methods for small data sets.
A table showing simulation results to determine analysis methods for small data sets
Carbonate chemistry of the two study reefs - means over tiles
Carbonate chemistry of the two study reefs - mean values for each of the settlement tiles
Densities of coral juveniles
Densities of coral juveniles at Dobu and Upa Upasina CO2 seep and Control sites
Substrata on settlement tiles
Substrata on settlement tiles including individual taxa of crustose coralline alga