normalize

Internal function for normalizing the data.
 This function makes a linear transformation of the inputs such that the values lie between -1 and 1.

models

Bayesian regularization for feed-forward neural networks.

Paulino Rodriguez

brnn

Bayesian Regularization for Feed-Forward Neural Networks

normalize function

<dl> <dt>x</dt>
<dd>a vector or matrix that needs to be normalized.</dd> <dt>base</dt>
<dd>If x is a vector, base is the minimum of x. If x is a matrix, base is a vector with the minimum for each of the columns of the matrix x.</dd> <dt>spread</dt>
<dd>if x is a vector, spread=max(x)-base. If x is a matrix, spread is a vector calculated for each of the columns of x.</dd></dl>

Arguments

normalize — normalize

<dl>

 <dt>x</dt>
<dd>a vector or matrix that needs to be normalized.</dd>

 <dt>base</dt>
<dd>If x is a vector, base is the minimum of x. If x is a matrix, base is a vector with the minimum for each of the columns of the matrix x.</dd>

 <dt>spread</dt>
<dd>if x is a vector, spread=max(x)-base. If x is a matrix, spread is a vector calculated for each of the columns of x.</dd>

</dl>

normalize: normalize

Description

Usage

Value

Arguments

Details