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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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : 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. N° de réf. du vendeur 9786139895779
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Etat : 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 . N° de réf. du vendeur 385876297
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Taschenbuch. Etat : 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. N° de réf. du vendeur 9786139895779
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Taschenbuch. Etat : 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. N° de réf. du vendeur 9786139895779
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