relu

Offers a flexible formula-based interface for building and training Bayesian Neural Networks powered by 'Stan'. The package supports modeling complex relationships while providing rigorous uncertainty quantification via posterior distributions. With features like user chosen priors, clear predictions, and support for regression, binary, and multi-class classification, it is well-suited for applications in clinical trials, finance, and other fields requiring robust Bayesian inference and decision-making. References: Neal(1996) <doi:10.1007/978-1-4612-0745-0>.

Swarnendu Chatterjee

bnns

Bayesian Neural Network with 'Stan'

relu function

<dl><dt>x</dt>
<dd>A numeric vector or matrix on which relu transformation is going to be applied.</dd></dl>

Arguments

relu transformation — relu

<dl>

<dt>x</dt>
<dd>A numeric vector or matrix on which relu transformation is going to be applied.</dd>

</dl>

relu: relu transformation

Description

Usage

Value

Arguments

Examples