Github user helenahm commented on the issue:
https://github.com/apache/incubator-hivemall/pull/93
I have also looked at the resulting models last week. Formally, I added
only one extra test to tests: hivemall.opennlp.tools.MaxEntPredictUDFTest.java.
/**
* Compare MaxEntropy in HiveMall with that of OpenNLP 3.0.0
*/
@Test
public void testResemblenceToOpenNLP() throws Exception {
}
The code inside the test gets access to internal model representation and
compares feature weights.
Using similar code I have looked at the feature weights in 3 models that
were relevant for my dataset. All the models look reasonable, that is, key
class features get high weights, and models predict what they should. One of
the models is an aggregated model (aggregated from the 302 I have got from
mappers). This one looks reasonable too.
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