Pinned Repositories
ClusteringLDA
ClusteringLDA has code to cluster topic distributions, to run LDA and to compute perplexity. The LDA code comes from Hannah Wallach's LDA development.
Evaluation-Methods-for-Topic-Models
Python implementations of some the algorithms in the paper: Evaluation Methods for Topic Models (Wallach et al.)
STM-SeqSTM
STM-SeqSTM has code to run Lan Du's STM, seqSTM and compute perplexity. This code is still under construction.
TopicGeographer
This app visualises, maps and compares topic distributions across geographical areas such as regions, local authorities and middle-layer super output areas! :). This app uses fictitious random data and the shapes files.
TopicOracle
This shiny app visualises and compares topics across time variables such as months, day of the week and hours.
naviInHyrule's Repositories
naviInHyrule/STM-SeqSTM
STM-SeqSTM has code to run Lan Du's STM, seqSTM and compute perplexity. This code is still under construction.
naviInHyrule/ClusteringLDA
ClusteringLDA has code to cluster topic distributions, to run LDA and to compute perplexity. The LDA code comes from Hannah Wallach's LDA development.
naviInHyrule/Evaluation-Methods-for-Topic-Models
Python implementations of some the algorithms in the paper: Evaluation Methods for Topic Models (Wallach et al.)
naviInHyrule/TopicGeographer
This app visualises, maps and compares topic distributions across geographical areas such as regions, local authorities and middle-layer super output areas! :). This app uses fictitious random data and the shapes files.
naviInHyrule/TopicOracle
This shiny app visualises and compares topics across time variables such as months, day of the week and hours.