cpopt: Find the optimal complexity parameter value
In annikacleven/regtreesegpackage: Segmenting CNV and BAF data using regression tree methods
Description
Usage
Arguments
Value
Author(s)
Examples
Description
The function finds the complexity parameter that is most optimal for reducing cross validation error.
Usage
1
Arguments
df
A dataframe with columns of Start.Pos and log2r
conserve
The default is FALSE. When TRUE the optimal complexity parameter has a minimum around .01 to reduce the chance of overfitting.
When FALSE the optimal complexity has a minimum around .001.
Value
The optimal complexity parameter in numeric format
Author(s)
Annika Cleven
Examples
1
2
annikacleven/regtreesegpackage documentation built on Dec. 19, 2021, 3:40 a.m.
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Description Usage Arguments Value Author(s) Examples
Description
The function finds the complexity parameter that is most optimal for reducing cross validation error.
Usage
1 |
Arguments
df |
A dataframe with columns of Start.Pos and log2r |
conserve |
The default is FALSE. When TRUE the optimal complexity parameter has a minimum around .01 to reduce the chance of overfitting. When FALSE the optimal complexity has a minimum around .001. |
Value
The optimal complexity parameter in numeric format
Author(s)
Annika Cleven
Examples
1 2 |
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.
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