gbm2x: The standard gradient boosted classifier for AndersenLab 2X...
In AndersenLab/easyXpress: A Package to Read, Process, and Analyze Worm Data Generated from CellProfiler’s WormToolbox
gbm2x R Documentation
The standard gradient boosted classifier for AndersenLab 2X images
Description
This stochastic gradient boosted classifier was trained with 1,089 worm objects selected from a broad range of experimental conditions
using the caret R package (v6.0-92) (Kuhn 2008). The classifier accuracy was 89.6
with 10-fold cross-validation.
Usage
gbm2x
Format
## 'gbm2x'
A Large train object with 24 elements.
Source
<https://github.com/AndersenLab/2021_GWA_data_cleaning>
AndersenLab/easyXpress documentation built on Dec. 6, 2024, 4:04 a.m.
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| gbm2x | R Documentation |
The standard gradient boosted classifier for AndersenLab 2X images
Description
This stochastic gradient boosted classifier was trained with 1,089 worm objects selected from a broad range of experimental conditions using the caret R package (v6.0-92) (Kuhn 2008). The classifier accuracy was 89.6 with 10-fold cross-validation.
Usage
gbm2x
Format
## 'gbm2x' A Large train object with 24 elements.
Source
<https://github.com/AndersenLab/2021_GWA_data_cleaning>
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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