Similarity-Based Adaptive Window for Improving Classification of Epileptic Seizures with Imbalance EEG Data Stream
Data stream mining techniques have recently received increasing research interest, especially in medical data classification. An unbalanced representation of the classification’s targets in these data is a common challenge because classification techniques are biased toward the major class. Many met...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-11-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/24/11/1641 |
| _version_ | 1797465389736656896 |
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| author | Hayder K. Fatlawi Attila Kiss |
| author_facet | Hayder K. Fatlawi Attila Kiss |
| author_sort | Hayder K. Fatlawi |
| collection | DOAJ |
| description | Data stream mining techniques have recently received increasing research interest, especially in medical data classification. An unbalanced representation of the classification’s targets in these data is a common challenge because classification techniques are biased toward the major class. Many methods have attempted to address this problem but have been exaggeratedly biased toward the minor class. In this work, we propose a method for balancing the presence of the minor class within the current window of the data stream while preserving the data’s original majority as much as possible. The proposed method utilized similarity analysis for selecting specific instances from the previous window. This group of minor-class was then added to the current window’s instances. Implementing the proposed method using the Siena dataset showed promising results compared to the Skew ensemble method and some other research methods. |
| first_indexed | 2024-03-09T18:20:45Z |
| format | Article |
| id | doaj.art-8b952c56992449cfb4b96191556e8cf9 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-09T18:20:45Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-8b952c56992449cfb4b96191556e8cf92023-11-24T08:18:28ZengMDPI AGEntropy1099-43002022-11-012411164110.3390/e24111641Similarity-Based Adaptive Window for Improving Classification of Epileptic Seizures with Imbalance EEG Data StreamHayder K. Fatlawi0Attila Kiss1Department of Information Systems, ELTE Eötvös Loránd University, 1117 Budapest, HungaryDepartment of Information Systems, ELTE Eötvös Loránd University, 1117 Budapest, HungaryData stream mining techniques have recently received increasing research interest, especially in medical data classification. An unbalanced representation of the classification’s targets in these data is a common challenge because classification techniques are biased toward the major class. Many methods have attempted to address this problem but have been exaggeratedly biased toward the minor class. In this work, we propose a method for balancing the presence of the minor class within the current window of the data stream while preserving the data’s original majority as much as possible. The proposed method utilized similarity analysis for selecting specific instances from the previous window. This group of minor-class was then added to the current window’s instances. Implementing the proposed method using the Siena dataset showed promising results compared to the Skew ensemble method and some other research methods.https://www.mdpi.com/1099-4300/24/11/1641machine learningsimilarity analysisEEGimbalanced data |
| spellingShingle | Hayder K. Fatlawi Attila Kiss Similarity-Based Adaptive Window for Improving Classification of Epileptic Seizures with Imbalance EEG Data Stream Entropy machine learning similarity analysis EEG imbalanced data |
| title | Similarity-Based Adaptive Window for Improving Classification of Epileptic Seizures with Imbalance EEG Data Stream |
| title_full | Similarity-Based Adaptive Window for Improving Classification of Epileptic Seizures with Imbalance EEG Data Stream |
| title_fullStr | Similarity-Based Adaptive Window for Improving Classification of Epileptic Seizures with Imbalance EEG Data Stream |
| title_full_unstemmed | Similarity-Based Adaptive Window for Improving Classification of Epileptic Seizures with Imbalance EEG Data Stream |
| title_short | Similarity-Based Adaptive Window for Improving Classification of Epileptic Seizures with Imbalance EEG Data Stream |
| title_sort | similarity based adaptive window for improving classification of epileptic seizures with imbalance eeg data stream |
| topic | machine learning similarity analysis EEG imbalanced data |
| url | https://www.mdpi.com/1099-4300/24/11/1641 |
| work_keys_str_mv | AT hayderkfatlawi similaritybasedadaptivewindowforimprovingclassificationofepilepticseizureswithimbalanceeegdatastream AT attilakiss similaritybasedadaptivewindowforimprovingclassificationofepilepticseizureswithimbalanceeegdatastream |