BrightWire.Net4 2.1.0

Bright Wire Machine Learning

Bright Wire is an open source machine learning library. Includes neural networks (feed forward, convolutional and recurrent), naive bayes, linear regression, decision trees, logistic regression, k-means clustering and dimensionality reduction.

There is a newer version of this package available.
See the version list below for details.
Install-Package BrightWire.Net4 -Version 2.1.0
dotnet add package BrightWire.Net4 --version 2.1.0
<PackageReference Include="BrightWire.Net4" Version="2.1.0" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add BrightWire.Net4 --version 2.1.0
The NuGet Team does not provide support for this client. Please contact its maintainers for support.

Breaking change: data table binary format updated (use CreateLegacyDataTable to load data tables from old format)
Breaking change: in place conversion of tensors, matrices and vectors now explicitly prefixed with "Reshape..."
Added: data table frequency analysis
Added: data table normalisation considers columns of type vector
Added: training data error calculation while training
Fixed: kmeans++ initialisation performance improved

Breaking change: data table binary format updated (use CreateLegacyDataTable to load data tables from old format)
Breaking change: in place conversion of tensors, matrices and vectors now explicitly prefixed with "Reshape..."
Added: data table frequency analysis
Added: data table normalisation considers columns of type vector
Added: training data error calculation while training
Fixed: kmeans++ initialisation performance improved

This package is not used by any popular GitHub repositories.

Version History

Version Downloads Last updated
2.1.1 170 2/23/2019
2.1.0 243 9/30/2018
2.0.6 212 7/27/2018
2.0.5 2,662 1/4/2018
2.0.4 433 9/23/2017
2.0.3 5,437 8/18/2017
2.0.2 507 6/21/2017
2.0.1 308 6/19/2017
2.0.0 243 6/7/2017
1.1.6 371 3/10/2017
1.1.5 248 3/3/2017
1.1.4 381 1/24/2017
1.1.3 285 1/19/2017
1.1.2 286 1/12/2017
1.1.1 322 12/8/2016
1.1.0 280 11/7/2016
1.0.8 255 10/31/2016
1.0.7 317 10/27/2016
1.0.5 279 10/25/2016
1.0.4 261 10/21/2016
1.0.3 269 10/18/2016
1.0.2 257 10/17/2016
1.0.1 263 10/14/2016
1.0.0 270 10/12/2016