July 28, 2019
LDA is a widely known model that finds topics in text. But, similar to k-means, you have to decide how many topics to look for. The stochastic nature of machine learning algorithms also causes the model to have instabilities, which results in topics being a mixture of multiple topics. This is the issue that led to the development of the “Ensemble LDA” model, which detects the stable topics in the text by using an ensemble of LDA topic models. The model detects and uses topic mixtures for stabilization.
It became part of gensim: https://github.com/RaRe-Technologies/gensim/pull/2980.
Thanks to aloosley for his support during the thesis and contributions to the PR.
Also thanks to mpenkov and radim for their code reviews and continuous interest in the work.