gbts: Hyperparameter Search for Gradient Boosted Trees

An implementation of hyperparameter optimization for Gradient Boosted Trees on binary classification and regression problems. The current version provides two optimization methods: Bayesian optimization and random search. Instead of giving the single best model, the final output is an ensemble of Gradient Boosted Trees constructed via the method of ensemble selection.

AuthorWaley W. J. Liang
Date of publication2017-02-27 08:41:32
MaintainerWaley W. J. Liang <wliang10@gmail.com>
LicenseGPL (>= 2) | file LICENSE
Version1.2.0

View on CRAN

Files

gbts
gbts/tests
gbts/tests/testthat.R
gbts/tests/testthat
gbts/tests/testthat/test-utility-acc.R
gbts/tests/testthat/test-utility-comperf.R
gbts/tests/testthat/test-utility-auc.R
gbts/tests/testthat/test-utility-ks.R
gbts/tests/testthat/test-utility-mae.R
gbts/tests/testthat/test-utility-dev.R
gbts/tests/testthat/test-utility-roc.R
gbts/tests/testthat/test-utility-mse.R
gbts/tests/testthat/test-utility-rsq.R
gbts/NAMESPACE
gbts/NEWS.md
gbts/data
gbts/data/boston_housing.RData
gbts/data/german_credit.RData
gbts/R
gbts/R/gbts.R gbts/R/data.R gbts/R/utility.R
gbts/README.md
gbts/MD5
gbts/DESCRIPTION
gbts/man
gbts/man/german_credit.Rd gbts/man/comperf.Rd gbts/man/predict.gbts.Rd gbts/man/gbts.Rd gbts/man/boston_housing.Rd
gbts/LICENSE

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