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dblr
View on CRAN: Click
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Download and install dblr package within the R console
Install from CRAN:
install.packages("dblr")
Install from Github:
library("remotes")
install_github("cran/dblr")
Install by package version:
library("remotes")
install_version("dblr", "0.1.0")
Attach the package and use:
library("dblr")
Maintained by
Nailong Zhang
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-10-11
Latest Update: 2017-10-11
Description:
Trains logistic regression model by discretizing continuous variables via gradient boosting approach. The proposed method tries to achieve a tradeoff between interpretation and prediction accuracy for logistic regression by discretizing the continuous variables. The variable binning is accomplished in a supervised fashion. The model trained by this package is still a single
logistic regression model, but not a sequence of logistic regression models. The fitted model
object returned from the model training consists of two tables. One table is used to give the
boundaries of bins for each continuous variable as well as the corresponding coefficients,
and the other one is used for discrete variables. This package can also be used for binning
continuous variables for other statistical analysis.
How to cite:
Nailong Zhang (2017). dblr: Discrete Boosting Logistic Regression. R package version 0.1.0, https://cran.r-project.org/web/packages/dblr
Previous versions and publish date:
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imports, suggests or enhances
Functions, R codes and Examples using
the dblr R package
Some associated functions: dblr_train . predict.dblr .
Some associated R codes: base.R . Full dblr package functions and examples
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