An adaptive online learning approach for Support Vector Regression: Online-SVR-FID

ZIO, ENRICO
2016-01-01

2016
Feature vector selection; Incremental and decremental learning; Online learning; Pattern drift; Support Vector Regression; Time series data; Mechanical Engineering; Civil and Structural Engineering; Aerospace Engineering; Control and Systems Engineering; Computer Science Applications1707 Computer Vision and Pattern Recognition; Signal Processing
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/985601
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