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mactivate (version 0.6.6)

Multiplicative Activation

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."

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Version

Install

install.packages('mactivate')

Monthly Downloads

214

Version

0.6.6

License

GPL (>= 3)

Maintainer

Dave Zes

Last Published

August 2nd, 2021

Functions in mactivate (0.6.6)

f_dmss_dW

Calculate Derivative of Cost Function wrt W
f_fit_gradient_01

Fit Multivariate Regression Model with mactivate Using Gradient Descent
predict.mactivate_fit_gradient_01

Predict from Fitted Gradient Model
mactivate-package

m-activation
f_fit_hybrid_01

Fit Multivariate Regression Model with mactivate Using Hybrid Method
f_fit_gradient_logistic_01

Fit Logistic Multivariate Regression Model with mactivate Using Gradient Descent
f_logit_cost

Logistic Cost
f_mactivate

Map Activation Layer and Inputs to Polynomial Model Inputs
df_hospitals_ortho

Orthopedic Device Sales
f_control_mactivate

Set Fitting Hyperparameters
predict.mactivate_fit_gradient_logistic_01

Predict from Fitted Gradient Logistic Model
predict.mactivate_fit_hybrid_01

Predict from Fitted Hybrid Model