A Parsimonious Mixture of Gaussian Trees Model for Oversampling in Imbalanced and Multimodal Time-Series Classification
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: 2014DOI: 10.1109/TNNLS.2014.2308321
Keyword(s): Gaussian processes,computational complexity,learning (artificial intelligence),pattern classification,sampling methods,time series,trees (mathematics),F-value metric,Gaussian trees model,classification accuracy,classification experiments,computational complexity,covariance parameters,imbalanced time-series classification,multimodal minority class,multimodal time-series classification,oversampling,parsimonious statistical model,support vector machines classifier,Computational m
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A Parsimonious Mixture of Gaussian Trees Model for Oversampling in Imbalanced and Multimodal Time-Series Classification
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| contributor author | Hong Cao | |
| contributor author | Tan, Vincent Y. F. | |
| contributor author | Pang, John Z. F. | |
| date accessioned | 2020-03-12T23:52:05Z | |
| date available | 2020-03-12T23:52:05Z | |
| date issued | 2014 | |
| identifier issn | 2162-237X | |
| identifier other | 6766252.pdf | |
| identifier uri | http://libsearch.um.ac.ir:80/fum/handle/fum/1126197 | |
| format | general | |
| language | English | |
| publisher | IEEE | |
| title | A Parsimonious Mixture of Gaussian Trees Model for Oversampling in Imbalanced and Multimodal Time-Series Classification | |
| type | Journal Paper | |
| contenttype | Metadata Only | |
| identifier padid | 8305987 | |
| subject keywords | Gaussian processes | |
| subject keywords | computational complexity | |
| subject keywords | learning (artificial intelligence) | |
| subject keywords | pattern classification | |
| subject keywords | sampling methods | |
| subject keywords | time series | |
| subject keywords | trees (mathematics) | |
| subject keywords | F-value metric | |
| subject keywords | Gaussian trees model | |
| subject keywords | classification accuracy | |
| subject keywords | classification experiments | |
| subject keywords | computational complexity | |
| subject keywords | covariance parameters | |
| subject keywords | imbalanced time-series classification | |
| subject keywords | multimodal minority class | |
| subject keywords | multimodal time-series classification | |
| subject keywords | oversampling | |
| subject keywords | parsimonious statistical model | |
| subject keywords | support vector machines classifier | |
| subject keywords | Computational m | |
| identifier doi | 10.1109/TNNLS.2014.2308321 | |
| journal title | Neural Networks and Learning Systems, IEEE Transactions on | |
| journal volume | 25 | |
| journal issue | 12 | |
| filesize | 3595369 | |
| citations | 1 |