is.HessMLP

Check if object is of class <code>HessMLP</code>

Analysis functions to quantify inputs importance in neural network models.
Functions are available for calculating and plotting the inputs importance and obtaining
the activation function of each neuron layer and its derivatives. The importance of a given
input is defined as the distribution of the derivatives of the output with respect to that
input in each training data point <doi:10.18637/jss.v102.i07>.

Jaime Pizarroso Gonzalo

NeuralSens

Sensitivity Analysis of Neural Networks

José Portela González

Antonio Muñoz San Roque

is.HessMLP function

<dl><dt>object</dt>
<dd><code>HessMLP</code> object</dd></dl>

Arguments

Check if object is of class HessMLP — is.HessMLP

<dl>

<dt>object</dt>
<dd><code>HessMLP</code> object</dd>

</dl>

is.HessMLP: Check if object is of class `HessMLP`

Description

Usage

Value

Arguments