A Parsimonious Mixture of Gaussian Trees Model for Oversampling in Imbalanced and Multimodal Time-Series Classification

نویسنده:
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ناشر:
سال
: 2014
شناسه الکترونیک: 10.1109/TNNLS.2014.2308321
کلیدواژه(گان): 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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