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Tribuo v4.1.1
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@Craigacp Craigacp released this 10 Dec 18:22
· 151 commits to main since this release
v4.1.1
cd6236a

This is the first patch release for Tribuo v4.1. The main fixes in this release are to the multi-dimensional output regression support, and to support the use of KMeans and KNN models when running under a restrictive SecurityManager. Additionally this release pulls in TensorFlow-Java 0.4.0 which upgrades the TensorFlow native library to 2.7.0 fixing several CVEs. Note those CVEs may not be applicable to TensorFlow-Java, as many of them relate to Python codepaths which are not included in TensorFlow-Java. Also note the TensorFlow upgrade is a breaking API change for Tribuo's TF API as graph initialization is handled differently in this release, which causes unavoidable changes.

Multi-dimensional Regression fix

In Tribuo 4.1.0 and earlier there is a severe bug in multi-dimensional regression models (i.e., regression tasks with multiple output dimensions). Models other than LinearSGDModel and SparseLinearModel (apart from when using the ElasticNetCDTrainer) have a bug in how the output dimension indices are constructed, and may produce incorrect outputs for all dimensions (as the output will be for a different dimension than the one named in the Regressor object). This has been fixed, and loading in models trained in earlier versions of Tribuo will patch the model to rearrange the dimensions appropriately. Unfortunately this fix cannot be applied to tree based models, and so all multi-output regression tree based models should be retrained using Tribuo 4.1.1 or newer as they are irretrievably corrupt. Additionally when using standardization in multi-output regression LibSVM models dimensions past the first dimension have the model improperly stored and will also need to be retrained with Tribuo 4.1.1 or newer. See #177 for more details.

Bug fixes

  • NPE fix for LIME explanations using models which don't support per class weights (#157).
  • Fixing a bug in multi-label evaluation which swapped FP for FN (#167).
  • Fixing LibSVM and LibLinear so they have reproducible behaviour (#172).
  • Provenance fix for TransformTrainer and an extra factory for XGBoostExternalModel so you can make them from an in memory booster (#176)
  • Fix multidimensional regression (#177) (fixes regression ids, fixes libsvm so it emits correct standardized models, adds support for per dimension feature weights in XGBoostRegressionModel).
  • Normalize LibSVMDataSource paths consistently in the provenance (#181).
  • KMeans and KNN now run correctly when using OpenSearch's SecurityManager (#197).
  • TensorFlow-Java 0.4.0 (#195).

Contributors

Full Changelog: v4.1.0...v4.1.1

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