Feature Selection Method Based On Hybrid Filter-Metaheuristic Wrapper Approach
High dimension data are often associated with redundant features and there exist many information-theoretic approaches used to select the most relevant set of features and to reduce the feature size. The three most significant approaches are filter, wrap- per, and embedded approaches. Most filter ap...
| المؤلف الرئيسي: | Jothi, Neesha |
|---|---|
| التنسيق: | أطروحة |
| اللغة: | الإنجليزية |
| منشور في: |
2020
|
| الموضوعات: | |
| الوصول للمادة أونلاين: | http://eprints.usm.my/52445/ |
| Abstract | Abstract here |
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مواد مشابهة
-
Short Text Classification Using An Enhanced Term Weighting Scheme And Filter-Wrapper Feature Selection
حسب: Alsmadi, Issa Mohammad Ibrahim
منشور في: (2018) -
Compute Language Interface: A Transparent Wrapper Library For Multi Cpu-Gpu
حسب: Ooi, Keng Siang
منشور في: (2013) -
Metaheuristic-Based Neural Network
Training And Feature Selector For
Intrusion Detection
حسب: Ghanem, Waheed Ali Hussein Mohammed
منشور في: (2019) -
Adapting And Hybrid Ising Harmony Search With Metaheuristic Components For University Course Timetabling
حسب: Al-Betar, Mohammed Azmi
منشور في: (2010) -
A Feature Selection Approach Based On Hybridizing Flower Pollination Algorithm With Particle Swarm Optimization For Enhancing The Performance Of Ipv6 Intrusion Detection System
حسب: Al Ghuraibawi, Adnan Hasan Bdair
منشور في: (2023)
