HetGSMOTE : a heterogeneous graph oversampling framework
Material type:
TextPublication details: Bhubaneswar : NISER, 2025. Description: vii, 35 pagesSubject(s): Synthetic minority oversampling technique | Graph neural network | Heterogeneous graphsDDC classification: 004.8 Online resources: Click here to access online
| Item type | Current library | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|
Dissertation (MSc)
|
NISER LIBRARY | 004.8 A-H (Browse shelf(Opens below)) | Not for loan | T960 |
Browsing NISER LIBRARY shelves Close shelf browser (Hides shelf browser)
| No cover image available | No cover image available | |||||||
| 004.7 VAL-N Network analysis | 004.732 PER-N Next generation wireless LANs 802.11n and 802.11ac | 004.77 BIA-M Multilayer networks: structure and function | 004.8 A-H HetGSMOTE : a heterogeneous graph oversampling framework | 004.8 BAR-S Selective, replay-consolidation memory for robust continual learning | 004.8 KOR-B Bayesian artificial intelligence | 004.8 LIU-P Python machine learning by example : |
There are no comments on this title.