gbmParallel

<code>gbmt</code> uses openmp to parallelize its core algorithm, and the
details are controlled by this object. As guidance, set
<code>num_threads</code> to the number of cores on your computer, and set
<code>array_chunk_size</code> to a reasonable - not necessarily small -
size.

Extensions to Freund and Schapire's AdaBoost algorithm, Y. Freund
and R. Schapire (1997) <doi:10.1006/jcss.1997.1504> and Friedman's gradient
boosting machine, J.H. Friedman (2001) <doi:10.1214/aos/1013203451>.
Includes regression methods for least squares, absolute loss,
t-distribution loss, quantile regression, logistic, Poisson,
Cox proportional hazards partial likelihood, AdaBoost
exponential loss, Huberized hinge loss,
and Learning to Rank measures (LambdaMART).

Ridgeway Greg

gbm3

Generalized Boosted Regression Models

James Hickey

Paul Metcalfe

Greg Ridgeway

Stefan Schroedl

Harry Southworth

Terry Therneau

gbmParallel function

<dl><dt>num_threads</dt>
<dd>the number of threads to use (a positive
integer). The number of cores on your computer is a
reasonable default.</dd>
<dt>array_chunk_size</dt>
<dd>the size of chunks to use in array scans.
Values that are too small result in a great deal of overhead;
The default of 1024 appears reasonable, but do experiment.</dd></dl>

Arguments

Control parallelization options — gbmParallel

<dl>

<dt>num_threads</dt>
<dd>the number of threads to use (a positive
integer). The number of cores on your computer is a
reasonable default.</dd>


<dt>array_chunk_size</dt>
<dd>the size of chunks to use in array scans.
Values that are too small result in a great deal of overhead;
The default of 1024 appears reasonable, but do experiment.</dd>

</dl>

gbmParallel: Control parallelization options

Description

Usage

Value

Arguments