Change point detection in time series data with random forests

Control Engineering Practice

Volumn 18, Issue 8, 2010, Pages 990-1002

  Auret, Lidia ^a   Aldrich, Chris ^a  

^a STELLENBOSCH UNIVERSITY   (South Africa)

Author keywords

Detection algorithms; Machine learning; Singular value decomposition; Subspace methods; Time series analysis

Indexed keywords

BINARY CLASSIFICATION PROBLEMS; CHANGE POINT DETECTION; CHANGE-POINTS; COMPLEX NONLINEAR SYSTEM; DETECTION ALGORITHM; DYNAMIC SYSTEMS; IN-PHASE; LARGE CLASS; MACHINE-LEARNING; MATRIX; MULTIVARIATE TIME SERIES; PROCESS CONDITION; PROXIMITY MATRIX; RANDOM FORESTS; SUB-SPACE METHODS; TIME-SERIES DATA; TRAJECTORY MATRIX;

DECISION TREES; DYNAMICAL SYSTEMS; FEATURE EXTRACTION; LEARNING ALGORITHMS; LEARNING SYSTEMS; SIGNAL DETECTION; SINGULAR VALUE DECOMPOSITION; TIME SERIES;

TIME SERIES ANALYSIS;

EID: 77955173484     PISSN: 09670661     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.conengprac.2010.04.005     Document Type: Article

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