NEWS.md

In gbts: Hyperparameter Search for Gradient Boosted Trees

gbts 1.2.0

• Implemented ensemble selection to construct an ensemble of models in the output of gbts().

• Revised the API of gbts() to simplify the specification of minimum and maximum values of hyperparameters.

• Improved the display of optimization progress.

• Terminated support for the R package "xgboost".

gbts 1.0.1

• Modified access to gbm predict() to be compatible with the current and next version of gbm.

• Revised the documentation of gbts() and the DESCRIPTION file to describe Bayesian optimization in replacement of active learning. This is merely a documentation change for the same algorithm.

• Allowed the "srch" argument of gbts() to accept "bayes" for Bayesian optimization.

• Revised the description of the "cutoff" argument of gbts().

• Changed R (>= 3.3.1) in the DESCRIPTION file to R (>= 3.3.0) to address the installation error from OS X on CRAN, which uses R version 3.3.0 at the time.

gbts 1.0.0

• This is the initial release.

gbts documentation built on May 2, 2019, 9:42 a.m.