Adam Pocock

I'm not sure I understand the question. At the moment Tribuo doesn't have any implementations of feature selection wrappers. To add one you need to implement `org.tribuo.FeatureSelector` with the desired...

I would pass the feature selection algorithm a dataset and have it split that internally, controlled by a parameter. DataSources should only be converted into Datasets, nothing should really be...

You should keep the test set used by the wrapper completely separate from the test set used to evaluate the final classifier, so you need to split your data into...

We can add that, though `SimpleTextDataSource` constrains the input format for the text to an internal format we'd been using for years and we had expected that most users would...

Tribuo doesn't have an implementation of fitting GMMs. We have a data generator that can sample from them to generate example data, but it can't fit that generator to a...

I've written a GMM implementation which is currently being debugged. Do you need the `gmdistribution` function as applied to only a distribution fit on data, or do you also want...

Ok. You'll be able to save the model and reuse it for future predictions, but extracting a distribution object like `MultivariateNormalDistribution` back out of it will be a little complicated...

If you have in memory data then you can use [ListDataSource](https://tribuo.org/learn/4.3/javadoc/org/tribuo/datasource/ListDataSource.html), along with a suitable function to convert your data into `Example` instances.

Tribuo needs to know what the mapping is from the feature names it produces to the feature indices that the ONNX model expects. If your model expects a feature vector...

Ok, so you'd want to make a Tribuo example containing those 7 features, with appropriate names. Those can be semantic ones if the features actually have names, or just `00`,...,`06`,...