Pre-Processing of Hyperspectral Images Using Nonlinear Filters

Behar, V.; Bogdanova, Valentina E.

doi:10.2478/itc-2013-0002

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2014

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“…If a base classifier set, which has classified every check sample correctly, is regarded as a transaction, the corresponding transactions of these all samples can comprise a transaction database TD [11][12][13][14]. While by processing the transaction database, we can easily obtain the base classifier combination (pattern) which appear frequently.…”

Section: The Strategy Of Selective Ensemble Pruning Based On Pattern mentioning

confidence: 99%

Study of Ensemble Pruning Algorithms Based on the Idea of Pattern Mining

Li¹

2014

TOCSJ

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At first the thesis introduces a new concept: coverage-based pattern mining. Then based on this concept, two ensemble pruning algorithms, CPM-EP and PMEP are put forward. By the algorithms we get candidate sub-patterns,and applies coverage pattern mining and a greedy strategy to acquire candidate target ensemble. Experiments show that pattern mining is an efficient selective integration strategy, able to obtain predictive ability, small-scale target integrated classifier, the paper presents that the CPM-EP and PMEP algorithm is able to meet the demand for online learning.

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Section: The Strategy Of Selective Ensemble Pruning Based On Pattern mentioning

confidence: 99%