LF_ApplyRegression Processing Resource

The regression application PR allows you to apply a regression model you already learned using the regression training PR. The PR has no init time parameters. Here are the runtime parameters:

• algorithmParameters — At application time, this runtime parameter is a catch-all for various currently undocumented switches that don’t warrant their own parameter.
• dataDirectory — Where is the model that you want to use saved on disk?
• inputASName — Input annotation set containing attributes
• instanceType — Annotation type to classify
• outputASName — Where to put the new classifications. Leave blank to put them on the instance.
• serverUrl (String, no default) if specified, will try to connect to the given URL and use the server there to get the predictions. See ServerForApplication for details.
• targetFeature — Which feature to write the classification onto. Leave blank to put it in the feature that was learned at training time.

AlgorithmParameters

If a serverUrl is specified and thus a HTTP server is used to carry out the classification, the following parameters are supported:

• -d or -dense: send the vectors in dense format, default is sparse format