Case Study: Aircraft accident Analysis using different classifiers: Data Mining: Case Study based Aircraft Accident Analysis using different Classifiers - Couverture souple
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Case Study: Aircraft accident Analysis using different classifiers
Edité par
LAP LAMBERT Academic Publishing Okt 2017, 2017
ISBN 10 : 3659123072
ISBN 13 : 9783659123078
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In real world datasets, lots of redundant and conflicting data exist. The performance of a classification algorithm in data mining is greatly affected by noisy information (i.e. redundant and conflicting). These parameters not only increase the cost of mining process, but also degrade the detection performance of the classifiers. They have to be removed to increase the efficiency and the accuracy of the classifiers. Data mining is a data analysis process which is performed for large volume of data. The methodology for evaluating risk and safety issues of aircraft accidents is proposed in this work. This work focuses on different feature selection techniques applied on the dataset of an airline database to understand and clean the dataset. The following evaluators are like CFS,CS,GR, Information Gain, OneR Attribute, PCA Transformer, ReliefF Attribute and SU Attribute used in this study in order to reduce the number of initial attributes. The classification algorithms such as Decision Tree (DT), Naive Bayes (NB), Artificial Neural Network (ANN), K-Nearest Neighbour (KNN) and Support Vector Machines (SVM) are used to predict the warning level of the component as the class attribute. 112 pp. Englisch. N° de réf. du vendeur 9783659123078
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Case Study: Aircraft accident Analysis using different classifiers
Edité par
LAP LAMBERT Academic Publishing, 2017
ISBN 10 : 3659123072
ISBN 13 : 9783659123078
Neuf
Couverture souple
Vendeur : moluna, Greven, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Christopher A. B. ArockiaDr.A.B.Arockia Christopher,AP(SG), IT, Dr.MCET, Pollachi, Coimbatore, TN, India. He received his PhD in Data mining under I&CE from Anna University Chennai, India. He is a member of IEEE. He has published mor. N° de réf. du vendeur 508653523
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Case Study: Aircraft accident Analysis using different classifiers
Edité par
LAP LAMBERT Academic Publishing Okt 2017, 2017
ISBN 10 : 3659123072
ISBN 13 : 9783659123078
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -In real world datasets, lots of redundant and conflicting data exist. The performance of a classification algorithm in data mining is greatly affected by noisy information (i.e. redundant and conflicting). These parameters not only increase the cost of mining process, but also degrade the detection performance of the classifiers. They have to be removed to increase the efficiency and the accuracy of the classifiers. Data mining is a data analysis process which is performed for large volume of data. The methodology for evaluating risk and safety issues of aircraft accidents is proposed in this work. This work focuses on different feature selection techniques applied on the dataset of an airline database to understand and clean the dataset. The following evaluators are like CFS,CS,GR, Information Gain, OneR Attribute, PCA Transformer, ReliefF Attribute and SU Attribute used in this study in order to reduce the number of initial attributes. The classification algorithms such as Decision Tree (DT), Naive Bayes (NB), Artificial Neural Network (ANN), K-Nearest Neighbour (KNN) and Support Vector Machines (SVM) are used to predict the warning level of the component as the class attribute.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 112 pp. Englisch. N° de réf. du vendeur 9783659123078
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Case Study: Aircraft accident Analysis using different classifiers : Data Mining: Case Study based Aircraft Accident Analysis using different Classifiers
Edité par
LAP LAMBERT Academic Publishing, 2017
ISBN 10 : 3659123072
ISBN 13 : 9783659123078
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In real world datasets, lots of redundant and conflicting data exist. The performance of a classification algorithm in data mining is greatly affected by noisy information (i.e. redundant and conflicting). These parameters not only increase the cost of mining process, but also degrade the detection performance of the classifiers. They have to be removed to increase the efficiency and the accuracy of the classifiers. Data mining is a data analysis process which is performed for large volume of data. The methodology for evaluating risk and safety issues of aircraft accidents is proposed in this work. This work focuses on different feature selection techniques applied on the dataset of an airline database to understand and clean the dataset. The following evaluators are like CFS,CS,GR, Information Gain, OneR Attribute, PCA Transformer, ReliefF Attribute and SU Attribute used in this study in order to reduce the number of initial attributes. The classification algorithms such as Decision Tree (DT), Naive Bayes (NB), Artificial Neural Network (ANN), K-Nearest Neighbour (KNN) and Support Vector Machines (SVM) are used to predict the warning level of the component as the class attribute. N° de réf. du vendeur 9783659123078
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Case Study: Aircraft accident Analysis using different classifiers | Data Mining: Case Study based Aircraft Accident Analysis using different Classifiers
Edité par
LAP LAMBERT Academic Publishing, 2017
ISBN 10 : 3659123072
ISBN 13 : 9783659123078
Neuf
Taschenbuch
Vendeur : preigu, Osnabrück, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. Case Study: Aircraft accident Analysis using different classifiers | Data Mining: Case Study based Aircraft Accident Analysis using different Classifiers | A. B. Arockia Christopher (u. a.) | Taschenbuch | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9783659123078 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. N° de réf. du vendeur 120552863
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