Exporting LightGBM to PMML, and then scoring using a Java PMML engine should count as a viable option in the meantime.

I've updated my JPMML-LightGBM exporter library to be fully compatible with the latest LightGBM v2.0.7 (including the handling of categorical/binary features and missing values). Better yet, it provides some custom functionality such as limiting the number of trees (similar to the num_iteration parameter of LightGBM's Scikit-Learn API), and compacting individual trees.

Tree compaction involves 1) expanding LightGBM-style binary splits into PMML-style multi-way splits, 2) eliminating half terminal nodes (aka leafs) and 3) eliminating redundant tree splitting predicates. It leads to >50% reduction in PMML file size.

Do you have the plan to support Java like xgboost4j? #909

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