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neuralGAM
View on CRAN: Click
here
Download and install neuralGAM package within the R console
Install from CRAN:
install.packages("neuralGAM")
Install from Github:
library("remotes")
install_github("cran/neuralGAM")
Install by package version:
library("remotes")
install_version("neuralGAM", "1.1.0")
Attach the package and use:
library("neuralGAM")
Maintained by
Ines Ortega-Fernandez
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-09-07
Latest Update: 2023-09-20
Description:
Neural network framework based on Generalized Additive Models from Hastie & Tibshirani (1990, ISBN:9780412343902), which trains a different neural network to estimate the contribution of each feature to the response variable. The networks are trained independently leveraging the local scoring and backfitting algorithms to ensure that the Generalized Additive Model converges and it is additive. The resultant Neural Network is a highly accurate and interpretable deep learning model, which can be used for high-risk AI practices where decision-making should be based on accountable and interpretable algorithms.
How to cite:
Ines Ortega-Fernandez (2023). neuralGAM: Interpretable Neural Network Based on Generalized Additive Models. R package version 1.1.0, https://cran.r-project.org/web/packages/neuralGAM
Other packages that cited neuralGAM R package
View neuralGAM citation profile
Other R packages that neuralGAM depends,
imports, suggests or enhances
Functions, R codes and Examples using
the neuralGAM R package
Some associated functions: autoplot.neuralGAM . build_feature_NN . dev . diriv . get_formula_elements . install_neuralGAM . inv_link . link . neuralGAM-package . neuralGAM . plot.neuralGAM . predict.neuralGAM . print.neuralGAM . reexports . summary.neuralGAM . weight .
Some associated R codes: NeuralGAM.R . autoplot.neuralGAM.R . build_feature_NN.R . dev.R . diriv.R . formula.R . install.R . inv_link.R . link.R . neuralGAM-package.R . plot.NeuralGAM.R . predict.NeuralGAM.R . print.NeuralGAM.R . summary.NeuralGAM.R . weight.R . Full neuralGAM package functions and examples
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