diriv

Computes the derivative of the link function according to
the distribution family specified in the <code>"family"</code> parameter.

internal

Neural Additive Model 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.

Ines Ortega-Fernandez

neuralGAM

Interpretable Neural Network Based on Generalized Additive
Models

Marta Sestelo

diriv function

<dl><dt>family</dt>
<dd>A description of the link function used in the model:
<code>"gaussian"</code>, <code>"poisson"</code>, or <code>"binomial"</code></dd>
<dt>muhat</dt>
<dd>fitted values</dd></dl>

Arguments

Ines Ortega-Fernandez, Marta Sestelo.

Author

Derivative of the link function — diriv

<dl>

<dt>family</dt>
<dd>A description of the link function used in the model:
<code>"gaussian"</code>, <code>"poisson"</code>, or <code>"binomial"</code></dd>


<dt>muhat</dt>
<dd>fitted values</dd>

</dl>

diriv: Derivative of the link function

Description

Usage

Value

Arguments

Author