Compression schemes for mining large datasets : a machine learning perspective /

Compression schemes for mining large datasets : a machine learning perspective /

As data mining algorithms are typically applied to sizable volumes of high-dimensional data, these can result in large storage requirements and inefficient computation times. This unique text/reference addresses the challenges of data abstraction generation using a least number of database scans, co...

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Wedi'i Gadw mewn:
Manylion Llyfryddiaeth
Prif Awduron: Ravindra Babu, T. (Awdur), Narasimha Murty, M. (Awdur), Subrahmanya, S.V (Awdur)
Awdur Corfforaethol: SpringerLink (Online service)
Fformat: eLyfr
Iaith:English
Cyhoeddwyd: London Springer London Imprint: Springer, 2013.
Cyfres:Advances in Computer Vision and Pattern Recognition,
Pynciau:
Computer science.
Data mining.
Artificial intelligence.
Optical pattern recognition.
Mynediad Ar-lein:Click here to view the full text content
Tagiau: Ychwanegu Tag
Dim Tagiau, Byddwch y cyntaf i dagio'r cofnod hwn!
Tabl Cynhwysion:
  • Introduction
  • Data Mining Paradigms
  • Run-Length Encoded Compression Scheme
  • Dimensionality Reduction by Subsequence Pruning
  • Data Compaction through Simultaneous Selection of Prototypes and Features
  • Domain Knowledge-Based Compaction
  • Optimal Dimensionality Reduction
  • Big Data Abstraction through Multiagent Systems
  • Intrusion Detection Dataset: Binary Representation.

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