package-ptf

ptf-package

package-ptf-package

<table><tr><td>
Package: </td>
<td> ptf </td>
</tr><tr><td>
Type: </td>
<td> Package</td>
</tr><tr><td>
Version: </td>
<td> 0.0.1</td>
</tr><tr><td>
Date: </td>
<td> 2020-09-30</td>
</tr><tr><td>
License: </td>
<td> GPL</td>
</tr><tr><td>
LazyLoad: </td>
<td> yes</td>
</tr><tr><td>
LazyData: </td>
<td> yes</td>
</tr></table>

model

tensor

factorization

Probit

Efficient algorithms to implement Probit Tensor Factorization (PTF) model for statistical relational learning, which not only inherits the computation efficiency from the classic tensor factorization model but also accounts for the binary nature of relational data. The methodology is based on Ye Liu (2021) <https://repository.lib.ncsu.edu/bitstream/handle/1840.20/37507/etd.pdf?sequence=1> "Computational Methods for Complex Models with Latent Structure".

package-ptf: probit tensor factorization

Description

Arguments

Package:	ptf
Type:	Package
Version:	0.0.1
Date:	2020-09-30
License:	GPL
LazyLoad:	yes
LazyData:	yes