Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Classification of imbalanced datasets remained a significant issue in data mining and machine learning (ML) fields. This research work proposed a new idea based on the optimization for handling the imbalanced datasets. A new self-adaptive hybrid algorithm (CSCMAES) is introduced for optimization....
Saved in:
Main Author: | Saeed, Sana |
---|---|
Format: | Thesis |
Language: | English |
Published: |
2019
|
Subjects: | |
Online Access: | http://eprints.usm.my/48598/1/Sana%20Saeed%20thesis%20Ph.D%20cut.pdf http://eprints.usm.my/48598/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Multi-objective Hybrid Election Algorithm For Random K Satisfiability In Discrete Hopfield Neural Network
by: Karim, Syed Anayet
Published: (2023) -
Eeg-Based Person Identification Using Multi-Levelwavelet Decomposition With Multi-Objective Flower Pollination Algorithm
by: Yahya Alyasseri, Zaid Abdi Alkareem
Published: (2020) -
Algorithms For Multi-Criteria Global Path Planning Of An Unmanned Combat Vehicle
by: Saw Hin, Saw Veekeong
Published: (2020) -
A Hybrid Neural Network - Hidden Markov Model - Fuzzy
Logic Method For Protein Classification
by: Chew, Martin Wooi Keat
Published: (2007) -
An Improved Wavelet Neural Network For Classification And Function Approximation
by: Ong , Pauline
Published: (2011)