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text-preprocessing

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lanl / T-ELF

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Tensor Extraction of Latent Features (T-ELF). Within T-ELF's arsenal are non-negative matrix and tensor factorization solutions, equipped with automatic model determination (also known as the estimation of latent factors - rank) for accurate data modeling. Our software suite encompasses cutting-edge data pre-processing and post-processing modules.

machine-learning hpc gpu matrix matrix-factorization feature-extraction high-performance-computing semi-supervised-learning dimensionality-reduction tensor-factorization tensors unsupervised-learning matrix-completion tensor-decomposition latent-variables blind-source-separation non-negative-matrix-factorization text-preprocessing pattern-extraction
  • Updated Jul 24, 2024
  • Python

bademiya21 / Topic-Modeling-with-Automated-Determination-of-the-Number-of-Topics

Star 14

My version of topic modelling using Latent Dirichlet Allocation (LDA) which finds the best number of topics for a set of documents using ldatuning package which comes with different metrics

visualization text-mining r metrics text topic-modeling text-processing lda unsupervised-learning probabilistic-graphical-models latent-dirichlet-allocation text-preprocessing
  • Updated Nov 15, 2018
  • R

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