Parallel Processing Framework for Minority Oversampling in Kernel Canonical Correlation Analysis (KCCA) Adaptive Subspaces for Class Imbalanced Datasets

Vishnu Prasad Krishnakumar

doi:10.5373/jardcs/v12sp4/20201487

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Parallel Processing Framework for Minority Oversampling in Kernel Canonical Correlation Analysis (KCCA) Adaptive Subspaces for Class Imbalanced Datasets

Vishnu Prasad Krishnakumar

Year: 2020 Journal: Journal of Advanced Research in Dynamical and Control Systems Vol: 12 (SP4)Pages: 250-261

DOI: 10.5373/jardcs/v12sp4/20201487

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Keywords:

Oversampling Linear subspace Kernel (algebra) Canonical correlation Class (philosophy) Computer science Correlation Artificial intelligence Theoretical computer science Pattern recognition (psychology) Mathematics Discrete mathematics Pure mathematics Bandwidth (computing)

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Imbalanced Data Classification Techniques

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Parallel Processing Framework for Minority Oversampling in Kernel Canonical Correlation Analysis (KCCA) Adaptive Subspaces for Class Imbalanced Datasets

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