Spark NLP for Healthcare Release Notes 2.4.6

 

2.4.6

Overview

We release Spark NLP for Healthcare 2.4.6 to fix some minor bugs.

Bugfixes

  • Updated IDF value calculation to be probabilistic based log[(N - df_t) / df_t + 1] as opposed to log[N / df_t]
  • TFIDF cosine distance was being calculated with the rooted norms rather than with the original squared norms
  • Validation of label cols is now performed at the beginning of EnsembleEntityResolver
  • Environment Variable for License value named jsl.settings.license
  • Now DocumentLogRegClassifier can be serialized from Python (bug introduced with the implementation of RecursivePipelines, LazyAnnotator attribute)

Versions

Last updated