Robust data mining | Perpustakaan Universitas Negeri Jakarta

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Robust data mining

Xanthopoulos, Petros - Nama Orang; Pardalos, Panos M. - Nama Orang; Trafalis, Theodore B. - Nama Orang;

Data uncertainty is a concept closely related with most real life applications that involve data collection and interpretation. Examples can be found in data acquired with biomedical instruments or other experimental techniques. Integration of robust optimization in the existing data mining techniques aim to create new algorithms resilient to error and noise.
This work encapsulates all the latest applications of robust optimization in data mining. This brief contains an overview of the rapidly growing field of robust data mining research field and presents the most well known machine learning algorithms, their robust counterpart formulations and algorithms for attacking these problems.
This brief will appeal to theoreticians and data miners working in this field.

Ketersediaan

Perpustakaan Pusat E434

E434

Tersedia

Informasi Detail

Judul Seri: -
No. Panggil: E434
Penerbit: New York : Springer., 2012
Deskripsi Fisik: xii, 59 hlm.
Bahasa: English
ISBN/ISSN: 9781441998781
Klasifikasi: NONE
Tipe Isi: text
Tipe Media: computer
Tipe Pembawa: online resource
Edisi: 1
Subjek: Algoritma Komputer
Info Detail Spesifik: -
Pernyataan Tanggungjawab: Petros Xanthopoulos , Panos M. Pardalos , Theodore B. Trafalis

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Lampiran Berkas

Robust Data Mining
https://doi.org/10.1007/978-1-4419-9878-1

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