Apache Mahout: Machine Learning on Distributed Dataflow Systems

Anil R., Capan G., Drost-Fromm I., Dunning T., Friedman E., Grant T., ...Daha Fazla

JOURNAL OF MACHINE LEARNING RESEARCH, cilt.21, 2020 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 21
  • Basım Tarihi: 2020
  • Dergi Adı: JOURNAL OF MACHINE LEARNING RESEARCH
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Compendex, Computer & Applied Sciences, MathSciNet, zbMATH
  • Anadolu Üniversitesi Adresli: Evet

Özet

APACHE MAHOUT is a library for scalable machine learning (ML) on distributed dataflow systems, offering various implementations of classification, clustering, dimensionality reduction and recommendation algorithms. Mahout was a pioneer in large-scale machine learning in 2008, when it started and targeted MapReduce, which was the predominant abstraction for scalable computing in industry at that time. Mahout has been widely used by leading web companies and is part of several commercial cloud offerings.