mactivate0.6.6 package

Multiplicative Activation

f_control_mactivate

Set Fitting Hyperparameters

f_dmss_dW

Calculate Derivative of Cost Function wrt W

f_fit_gradient_01

Fit Multivariate Regression Model with mactivate Using Gradient Descen...

f_fit_gradient_logistic_01

Fit Logistic Multivariate Regression Model with mactivate Using Gradie...

f_fit_hybrid_01

Fit Multivariate Regression Model with mactivate Using Hybrid Method

f_logit_cost

Logistic Cost

f_mactivate

Map Activation Layer and Inputs to Polynomial Model Inputs

mactivate-package

m-activation

predict.mactivate_fit_gradient_01

Predict from Fitted Gradient Model

predict.mactivate_fit_gradient_logistic_01

Predict from Fitted Gradient Logistic Model

predict.mactivate_fit_hybrid_01

Predict from Fitted Hybrid Model

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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."

  • Maintainer: Dave Zes
  • License: GPL (>= 3)
  • Last published: 2021-08-02