Electroencephalography signal classification using neural network, decision tree and ensemble bagged tree for epilepsy disease
Epilepsy is a brain disease caused by abnormal brain activities. Machine learning algorithms are usually applied in the classification and identification of epilepsy at an early stage. This study's primary objective is to classify the Electroencephalography (EEG) signal dataset of epileptic sei...
Saved in:
主要作者: | Abdul Aziz, Nur Syahirah |
---|---|
格式: | Thesis |
語言: | English |
出版: |
2022
|
主題: | |
在線閱讀: | http://eprints.utm.my/id/eprint/102291/1/NurSyahirahAbdulAzizMFS2022.pdf.pdf |
標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
相似書籍
-
Cost-sensitive ensemble decision tree algorithms for customer churn analysis
由: Wong, Keng Tuck
出版: (2020) -
Spatial analysis of signal during epileptic seizure on plat electroencephalography
由: Goh, Chien Yong
出版: (2017) -
Jordan-chevalley decomposition of recorded electroencephalography signals during epileptic seizures
由: Ahmad Fuad, Amirul Aizad
出版: (2021) -
Classification of electroencephalography signal using statistical features and regression classifier
由: Sabri, Nurbaity
出版: (2014) -
Classification of electroencephalography signal using statistical features and regression classifier
由: Sabri, Nurbaity
出版: (2014)