LightLDA is a distributed system for large scale topic modeling. It implements a distributed sampler that enables very large data sizes and models. LightLDA improves sampling throughput and convergence speed via a fast O(1) metropolis-Hastings algorithm, and allows small cluster to tackle very large data and model sizes through model scheduling and data parallelism architecture. LightLDA is implemented with C++ for performance consideration.

lightlda-master
...............\.gitignore
...............\LICENSE
...............\Makefile
...............\README.md
...............\build.sh
...............\example
...............\.......\README.md
...............\.......\get_meta.py
...............\.......\nytimes.sh
...............\.......\pubmed.sh
...............\.......\text2libsvm.py
...............\inference
...............\.........\infer.cpp
...............\.........\inferer.cpp
...............\.........\inferer.h
...............\preprocess
...............\..........\dump_binary.cpp
...............\src
...............\...\alias_table.cpp
...............\...\alias_table.h
...............\...\common.cpp
...............\...\common.h
...............\...\data_block.cpp
...............\...\data_block.h
...............\...\data_stream.cpp
...............\...\data_stream.h
...............\...\document.cpp
...............\...\document.h
...............\...\eval.cpp
...............\...\eval.h
...............\...\lightlda.cpp
...............\...\meta.cpp
...............\...\meta.h
...............\...\model.cpp
...............\...\model.h
...............\...\sampler.cpp
...............\...\sampler.h
...............\...\trainer.cpp
...............\...\trainer.h
...............\...\util.h
...............\windows
...............\.......\README.md
...............\.......\dump_binary
...............\.......\...........\dump_binary.vcxproj
...............\.......\infer
...............\.......\.....\infer.vcxproj
...............\.......\lightlda.sln
...............\.......\lightlda
...............\.......\........\lightlda.vcxproj

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