This book is mainly for the students of machine learning. This book also addresses the needs of the researchers who work in the knowledge field of bio-medical imaging and computer assisted oncology. This book demonstrates a holistic approach of malignant tumor classification via machine learning. It enumerates different stages of image analysis and image segmentation with the help of MATLAB code. WEKA data mining software has been used to describe both supervised and unsupervised learning methods. Each and every phase of tumor classification: feature extraction, data pre-processing, attribute selection, classification and model evaluation has been properly explained with the help of screenshots. It has also been depicted that, how the users may use python to execute such classification tasks.I hope this book will help the students, researchers as well as teachers working on machine learning as a ready reference.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book is mainly for the students of machine learning. This book also addresses the needs of the researchers who work in the knowledge field of bio-medical imaging and computer assisted oncology. This book demonstrates a holistic approach of malignant tumor classification via machine learning. It enumerates different stages of image analysis and image segmentation with the help of MATLAB code. WEKA data mining software has been used to describe both supervised and unsupervised learning methods. Each and every phase of tumor classification: feature extraction, data pre-processing, attribute selection, classification and model evaluation has been properly explained with the help of screenshots. It has also been depicted that, how the users may use python to execute such classification tasks.I hope this book will help the students, researchers as well as teachers working on machine learning as a ready reference. 56 pp. Englisch. Codice articolo 9786139475001
Quantità: 2 disponibili
Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. Codice articolo 26395825707
Quantità: 4 disponibili
Da: Majestic Books, Hounslow, Regno Unito
Condizione: New. Print on Demand. Codice articolo 400584180
Quantità: 4 disponibili
Da: Biblios, Frankfurt am main, HESSE, Germania
Condizione: New. PRINT ON DEMAND. Codice articolo 18395825697
Quantità: 4 disponibili
Da: Revaluation Books, Exeter, Regno Unito
Paperback. Condizione: Brand New. 56 pages. 8.66x5.91x0.13 inches. In Stock. Codice articolo zk6139475007
Quantità: 1 disponibili
Da: moluna, Greven, Germania
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Moitra DipanjanMr. Dipanjan Moitra is an IT faculty in the Department of Management, University of North Bengal, India. He completed his MCA from IGNOU in 2005. He has authored several research papers on machine learning and also aut. Codice articolo 293476494
Quantità: Più di 20 disponibili
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book is mainly for the students of machine learning. This book also addresses the needs of the researchers who work in the knowledge field of bio-medical imaging and computer assisted oncology. This book demonstrates a holistic approach of malignant tumor classification via machine learning. It enumerates different stages of image analysis and image segmentation with the help of MATLAB code. WEKA data mining software has been used to describe both supervised and unsupervised learning methods. Each and every phase of tumor classification: feature extraction, data pre-processing, attribute selection, classification and model evaluation has been properly explained with the help of screenshots. It has also been depicted that, how the users may use python to execute such classification tasks.I hope this book will help the students, researchers as well as teachers working on machine learning as a ready reference.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 56 pp. Englisch. Codice articolo 9786139475001
Quantità: 1 disponibili
Da: AHA-BUCH GmbH, Einbeck, Germania
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book is mainly for the students of machine learning. This book also addresses the needs of the researchers who work in the knowledge field of bio-medical imaging and computer assisted oncology. This book demonstrates a holistic approach of malignant tumor classification via machine learning. It enumerates different stages of image analysis and image segmentation with the help of MATLAB code. WEKA data mining software has been used to describe both supervised and unsupervised learning methods. Each and every phase of tumor classification: feature extraction, data pre-processing, attribute selection, classification and model evaluation has been properly explained with the help of screenshots. It has also been depicted that, how the users may use python to execute such classification tasks.I hope this book will help the students, researchers as well as teachers working on machine learning as a ready reference. Codice articolo 9786139475001
Quantità: 1 disponibili
Da: preigu, Osnabrück, Germania
Taschenbuch. Condizione: Neu. Classification of Malignant Tumors: A Practical Approach | Dipanjan Moitra | Taschenbuch | 56 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786139475001 | Verantwortliche Person für die EU: LAP Lambert Academic Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu Print on Demand. Codice articolo 116798307
Quantità: 5 disponibili