GC-LDA specifications

Information


Unique identifier OMICS_23045
Name GC-LDA
Alternative name Generalized Correspondence Latent Dirichlet Allocation
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages Python
Computer skills Advanced
Stability Stable
Maintained Yes

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Maintainer


  • person_outline Tal Yarkoni <>

Publication for Generalized Correspondence Latent Dirichlet Allocation

GC-LDA institution(s)
Department of Psychological and Brain Sciences, Indiana University Bloomington, Bloomington, IN, USA; SurveyMonkey, San Mateo, CA, USA; Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, USA; Department of Psychology, Stanford University, Stanford, CA, USA; Department of Psychology, Stanford University, Stanford, CA, USA
GC-LDA funding source(s)
Supported by National Institute of Mental Health award R01MH096906.

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