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Applying machine learning for automated classification of biomedical data in subject-independent settings

Pham, Thuy T.; (Springer Cham, 2019)

 Abstrak

This book describes efforts to improve subject-independent automated classification techniques using a better feature extraction method and a more efficient model of classification. It evaluates three popular saliency criteria for feature selection, showing that they share common limitations, including time-consuming and subjective manual de-facto standard practice, and that existing automated efforts have been predominantly used for subject dependent setting. It then proposes a novel approach for anomaly detection, demonstrating its effectiveness and accuracy for automated classification of biomedical data, and arguing its applicability to a wider range of unsupervised machine learning applications in subject-independent settings.

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 Metadata

Jenis Koleksi : eBooks
No. Panggil : e20502439
Entri utama-Nama orang :
Subjek :
Penerbitan : Switzerland: Springer Cham, 2019
Sumber Pengatalogan: LibUI eng rda
Tipe Konten: text
Tipe Media: computer
Tipe Pembawa: online resource
Deskripsi Fisik: xv, 107 pages : illustration
Tautan: http://link.springer.com/openurl?genre=book&isbn=978-3-319-98675-3
Lembaga Pemilik:
Lokasi:
  • Ketersediaan
  • Ulasan
  • Sampul
No. Panggil No. Barkod Ketersediaan
e20502439 20-23-64047103 TERSEDIA
Ulasan:
Tidak ada ulasan pada koleksi ini: 9999920521326
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