Streaming chunk incremental learning for class-wise data stream classification with fast learning speed and low structural complexity

Due to the fast speed of data generation and collection from advanced equipment, the amount of data obviously overflows the limit of available memory space and causes difficulties achieving high learning accuracy. Several methods based on discard-after-learn concept have been proposed. Some methods...

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Veröffentlicht in:	PloS one 2019-09, Vol.14 (9), p.e0220624-e0220624
Hauptverfasser:	Junsawang, Prem, Phimoltares, Suphakant, Lursinsap, Chidchanok
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial intelligence Artificial neural networks Basis functions Biology and Life Sciences Cluster Analysis Complexity Computational efficiency Computational neuroscience Computer and Information Sciences Computing time Confidence intervals Data transmission Datasets Datasets as Topic Humans Learning Neural networks Neural Networks, Computer Neurons Physical Sciences Recursive functions Research and Analysis Methods Social Sciences Statistical analysis Statistical methods Stream classification Supervised Machine Learning - statistics & numerical data Teaching methods
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