problem.joint.targets.train: problem joint targets train
In tdhock/PeakSegPipeline: Genome-Wide Peak Prediction Using Supervised Learning and Optimal Segmentation
Description
Usage
Arguments
Value
Author(s)
Description
Compute all joint target intervals then learn joint penalty
functions, in parallel over problems using
psp_lapply.
Usage
1
2
3
problem.joint.targets.train(data.dir,
verbose = getOption("PeakSegPipeline.verbose",
1))
Arguments
data.dir
project directory.
verbose
Value
Nothing.
Author(s)
Toby Dylan Hocking
tdhock/PeakSegPipeline documentation built on March 3, 2020, 1:35 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description Usage Arguments Value Author(s)
Description
Compute all joint target intervals then learn joint penalty
functions, in parallel over problems using
psp_lapply.
Usage
1 2 3 | problem.joint.targets.train(data.dir,
verbose = getOption("PeakSegPipeline.verbose",
1))
|
Arguments
data.dir |
project directory. |
verbose |
Value
Nothing.
Author(s)
Toby Dylan Hocking
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.