build_BBQ: build_BBQ
In CalibratR: Mapping ML Scores to Calibrated Predictions
Description
Usage
Arguments
Details
Value
Description
This method builds a BBQ calibration model using the trainings set provided.
Usage
1
build_BBQ(actual, predicted)
Arguments
actual
vector of observed class labels (0/1)
predicted
vector of uncalibrated predictions
Details
Based on the paper (and matlab code) : "Obtaining Well Calibrated Probabilities Using Bayesian Binning" by Naeini, Cooper and Hauskrecht: ; https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4410090/
Value
returns the BBQ model which includes models for all evaluated binning schemes; the prunedmodel contains only a selection of BBQ models with the best Bayesian score
CalibratR documentation built on Aug. 19, 2019, 5:04 p.m.
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Description Usage Arguments Details Value
Description
This method builds a BBQ calibration model using the trainings set provided.
Usage
1 | build_BBQ(actual, predicted)
|
Arguments
actual |
vector of observed class labels (0/1) |
predicted |
vector of uncalibrated predictions |
Details
Based on the paper (and matlab code) : "Obtaining Well Calibrated Probabilities Using Bayesian Binning" by Naeini, Cooper and Hauskrecht: ; https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4410090/
Value
returns the BBQ model which includes models for all evaluated binning schemes; the prunedmodel contains only a selection of BBQ models with the best Bayesian score
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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