Synopsis
Bio-informatics becomes more popular now-a-days as to combine medical problems with the information technology technical field to identify or to detect the medical disorders in the human body. This field is valuable for both the medical practitioners as well as software developers. To identify the brain disorders like epilepsy, parasomnias in the patients, EEG data is fetched from physionet data source where numbers of datasets are available for researchers. The analysis of this dataset is done by polyman which is used as plotting libraries and transformation tool for transforming the EDF data format into ASCII data format. The tool also helps in identifying the different parameters which are useful for predictions related to brain disorders. In this work, improved algorithm Support Vector Regression (SVR) has been developed and implemented using advanced python programming language and compared with classical Support vector Machine (SVM) algorithm. Results show better performance of SVR than SVM in terms of both complexity and execution time.
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An Approach towards Evaluation of EEG Dataset for Sleep Data Analysis
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LAP LAMBERT Academic Publishing Aug 2018, 2018
ISBN 10: 6139895774
ISBN 13: 9786139895779
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Bio-informatics becomes more popular now-a-days as to combine medical problems with the information technology technical field to identify or to detect the medical disorders in the human body. This field is valuable for both the medical practitioners as well as software developers. To identify the brain disorders like epilepsy, parasomnias in the patients, EEG data is fetched from physionet data source where numbers of datasets are available for researchers. The analysis of this dataset is done by polyman which is used as plotting libraries and transformation tool for transforming the EDF data format into ASCII data format. The tool also helps in identifying the different parameters which are useful for predictions related to brain disorders. In this work, improved algorithm Support Vector Regression (SVR) has been developed and implemented using advanced python programming language and compared with classical Support vector Machine (SVM) algorithm. Results show better performance of SVR than SVM in terms of both complexity and execution time. 64 pp. Englisch. Seller Inventory # 9786139895779
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An Approach towards Evaluation of EEG Dataset for Sleep Data Analysis
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ISBN 10: 6139895774
ISBN 13: 9786139895779
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An Approach towards Evaluation of EEG Dataset for Sleep Data Analysis
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Arora HeenaHeena Arora is a research Scholar in Information Technology department of Guru Nanak Dev Engineering College Ludhiana. Her research area are Data Mining, Knowledge Discovery and Bioinformatics.Bio-informatics becomes . Seller Inventory # 385876297
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An Approach towards Evaluation of EEG Dataset for Sleep Data Analysis
Published by
LAP LAMBERT Academic Publishing Aug 2018, 2018
ISBN 10: 6139895774
ISBN 13: 9786139895779
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Bio-informatics becomes more popular now-a-days as to combine medical problems with the information technology technical field to identify or to detect the medical disorders in the human body. This field is valuable for both the medical practitioners as well as software developers. To identify the brain disorders like epilepsy, parasomnias in the patients, EEG data is fetched from physionet data source where numbers of datasets are available for researchers. The analysis of this dataset is done by polyman which is used as plotting libraries and transformation tool for transforming the EDF data format into ASCII data format. The tool also helps in identifying the different parameters which are useful for predictions related to brain disorders. In this work, improved algorithm Support Vector Regression (SVR) has been developed and implemented using advanced python programming language and compared with classical Support vector Machine (SVM) algorithm. Results show better performance of SVR than SVM in terms of both complexity and execution time.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch. Seller Inventory # 9786139895779
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An Approach towards Evaluation of EEG Dataset for Sleep Data Analysis
Published by
LAP LAMBERT Academic Publishing, 2018
ISBN 10: 6139895774
ISBN 13: 9786139895779
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Bio-informatics becomes more popular now-a-days as to combine medical problems with the information technology technical field to identify or to detect the medical disorders in the human body. This field is valuable for both the medical practitioners as well as software developers. To identify the brain disorders like epilepsy, parasomnias in the patients, EEG data is fetched from physionet data source where numbers of datasets are available for researchers. The analysis of this dataset is done by polyman which is used as plotting libraries and transformation tool for transforming the EDF data format into ASCII data format. The tool also helps in identifying the different parameters which are useful for predictions related to brain disorders. In this work, improved algorithm Support Vector Regression (SVR) has been developed and implemented using advanced python programming language and compared with classical Support vector Machine (SVM) algorithm. Results show better performance of SVR than SVM in terms of both complexity and execution time. Seller Inventory # 9786139895779
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An Approach towards Evaluation of EEG Dataset for Sleep Data Analysis
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LAP LAMBERT Academic Publishing, 2018
ISBN 10: 6139895774
ISBN 13: 9786139895779
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Taschenbuch. Condition: Neu. An Approach towards Evaluation of EEG Dataset for Sleep Data Analysis | Heena Arora (u. a.) | Taschenbuch | 64 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9786139895779 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 114448599