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mactivate
View on CRAN: Click
here
Download and install mactivate package within the R console
Install from CRAN:
install.packages("mactivate")
Install from Github:
library("remotes")
install_github("cran/mactivate") Install by package version:
library("remotes")
install_version("mactivate", "0.6.6") Attach the package and use:
library("mactivate")
Maintained by
Dave Zes
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-01-08
Latest Update: 2021-08-02
Description:
Provides methods and classes for adding m-activation ("multiplicative activation") layers to MLR or multivariate logistic regression models. M-activation layers created in this library detect and add input interaction (polynomial) effects into a predictive model. M-activation can detect high-order interactions -- a traditionally non-trivial challenge. Details concerning application, methodology, and relevant survey literature can be found in this library's vignette, "About."
How to cite:
Dave Zes (2021). mactivate: Multiplicative Activation. R package version 0.6.6, https://cran.r-project.org/web/packages/mactivate. Accessed 06 Jun. 2026.
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imports, suggests or enhances
Complete documentation for mactivate
Functions, R codes and Examples using
the mactivate R package
Some associated functions: df_hospitals_ortho . f_control_mactivate . f_dmss_dW . f_fit_gradient_01 . f_fit_gradient_logistic_01 . f_fit_hybrid_01 . f_logit_cost . f_mactivate . mactivate-package . predict.mactivate_fit_gradient_01 . predict.mactivate_fit_gradient_logistic_01 . predict.mactivate_fit_hybrid_01 .
Some associated R codes: f_control_mactivate.R . f_dmss_dW.R . f_fit_gradient_01.R . f_fit_gradient_logistic_01.R . f_fit_hybrid_01.R . f_logit_cost.R . f_mactivate.R . predict.mactivate_fit_gradient_01.R . predict.mactivate_fit_gradient_logistic_01.R . predict.mactivate_fit_hybrid_01.R . Full mactivate package functions and examples
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