Graph Data Mining : Algorithm, Security and Application /
Contiene: 1) Estimación de fuente de información con red neuronal gráfica multicanal; 2) Predicción de enlace basada en red de alta estructura; 3) Aprendizaje amplio basado en redes de subgrafos para clasificación de grafos; 4) Aumento de subgrafos con aplicación a minería de grafos; 5) Ataques adve...
Furkejuvvon:
| Váldodahkki: | |
|---|---|
| Eará dahkkit: | , |
| Materiálatiipa: | Girji |
| Giella: | eaŋgalasgiella |
| Almmustuhtton: |
Singapur :
Springer,
2021, c2021
|
| Fáttát: | |
| Liŋkkat: | Ver documento en línea |
| Fáddágilkorat: |
Eai fáddágilkorat, Lasit vuosttaš fáddágilkora!
|
Geahča maid: Graph Data Mining :
- Algorithms and Computation : 24th International Symposium, ISAAC 2013 Hong Kong, China, December 16-18, 2013 Proceedings /
- Feature Engineering for Machine Learning and Data Analytics /
- Feature Engineering for Machine Learning : Principles and Techniques for Data Scientists /
- Feature Engineering for Machine Learning : Principles and Techniques for Data Scientists /
- Codeless Deep Learning with KNIME : Build, Train, and Deploy Various Deep Neural Network Architectures Using KNIME Analytics Platform /
- Feature Engineering Made Easy : Identify Unique Features From Your Dataset in Order to Build Powerful Machine Learning Systems /