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New R package 'nnmf' offers performance comparison for non-negative matrix factorization

By PulseAugur Editorial · [1 sources] ·

A new R package named nnmf has been developed for non-negative matrix factorization (NMF), a technique used for dimensionality reduction across various fields like bioinformatics, text mining, and image analysis. This study introduces the package and provides a performance comparison with two existing R packages for NMF. The evaluation uses real-world data to assess computational efficiency, convergence, accuracy, and stability, aiming to offer researchers objective guidance for selecting appropriate NMF tools. AI

IMPACT Provides a new tool and comparative analysis for NMF, potentially improving research efficiency in fields like text mining and recommender systems.

RANK_REASON The item is an academic paper detailing a new software package and its comparative analysis. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv stat.ML →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New R package 'nnmf' offers performance comparison for non-negative matrix factorization

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The item is an academic paper detailing a new software package and its comparative analysis. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. arXiv stat.ML TIER_1 English(EN) · Volkan Sevin\c{c}, Nikolas Kontemeniotis, Theodoros Perdikis, Michail Tsagris ·

    Non--negative matrix factorization using the \textit{R} package \textsf{nnmf}

    arXiv:2607.20084v1 Announce Type: new Abstract: Non--negative matrix factorization (NMF) has become an established dimensionality reduction technique for extracting latent structures from non--negative data and has found widespread applications in fields such as bioinformatics, t…

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