A Supervised Learning Approach for Criminal Identification: Using Similarity Measures and K-Medoids Clustering - Softcover
Synopsis
Data mining tools are best approach for Criminal identification based on characteristic and nature of crime. In this book, we have proposed a supervised approach for identifying the suspected list of criminal’s using similarity measure and K-Medoids cluster algorithm. K-Medoids clustering algorithm groups the more closely related crimes as an individual group and each group will have unique set of features. The unique features set is used for identification of criminal using similarity measure algorithms based on distance measure. The proposed system has two phase, training and testing phase. In this approach, we have trained the proposed system with supervised data set with collected crime information from various places of Tamil Nadu through online available data. In the testing phase, first identify the cluster closest to the test crime by using K-Medoids clustering algorithm and then identify the suspected criminal list using similarity measure. The initial stage of implementation and analysis of the proposed scheme provides good results and high accuracy. The proposed scheme is compared with related K-Means clustering algorithm with same set of training and test instances.
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A Supervised Learning Approach for Criminal Identification
Published by
LAP LAMBERT Academic Publishing Aug 2018, 2018
ISBN 10: 6139893178
ISBN 13: 9786139893171
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Data mining tools are best approach for Criminal identification based on characteristic and nature of crime. In this book, we have proposed a supervised approach for identifying the suspected list of criminal's using similarity measure and K-Medoids cluster algorithm. K-Medoids clustering algorithm groups the more closely related crimes as an individual group and each group will have unique set of features. The unique features set is used for identification of criminal using similarity measure algorithms based on distance measure. The proposed system has two phase, training and testing phase. In this approach, we have trained the proposed system with supervised data set with collected crime information from various places of Tamil Nadu through online available data. In the testing phase, first identify the cluster closest to the test crime by using K-Medoids clustering algorithm and then identify the suspected criminal list using similarity measure. The initial stage of implementation and analysis of the proposed scheme provides good results and high accuracy. The proposed scheme is compared with related K-Means clustering algorithm with same set of training and test instances. 56 pp. Englisch. Seller Inventory # 9786139893171
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A Supervised Learning Approach for Criminal Identification: Using Similarity Measures and K-Medoids Clustering
Published by
LAP LAMBERT Academic Publishing, 2018
ISBN 10: 6139893178
ISBN 13: 9786139893171
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A Supervised Learning Approach for Criminal Identification
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LAP LAMBERT Academic Publishing, 2018
ISBN 10: 6139893178
ISBN 13: 9786139893171
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Balasundaram IndraniShe has completed his BSc and MSc in Computer Science under Madurai Kamaraj University, Madurai, She has completed her PhD in the field of Computer Science at Alagappa University, Karaikudi, Now She is working as . Seller Inventory # 385876168
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A Supervised Learning Approach for Criminal Identification
Published by
LAP LAMBERT Academic Publishing Aug 2018, 2018
ISBN 10: 6139893178
ISBN 13: 9786139893171
New
Taschenbuch
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
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Taschenbuch. Condition: Neu. Neuware -Data mining tools are best approach for Criminal identification based on characteristic and nature of crime. In this book, we have proposed a supervised approach for identifying the suspected list of criminal¿s using similarity measure and K-Medoids cluster algorithm. K-Medoids clustering algorithm groups the more closely related crimes as an individual group and each group will have unique set of features. The unique features set is used for identification of criminal using similarity measure algorithms based on distance measure. The proposed system has two phase, training and testing phase. In this approach, we have trained the proposed system with supervised data set with collected crime information from various places of Tamil Nadu through online available data. In the testing phase, first identify the cluster closest to the test crime by using K-Medoids clustering algorithm and then identify the suspected criminal list using similarity measure. The initial stage of implementation and analysis of the proposed scheme provides good results and high accuracy. The proposed scheme is compared with related K-Means clustering algorithm with same set of training and test instances.Books on Demand GmbH, Überseering 33, 22297 Hamburg 56 pp. Englisch. Seller Inventory # 9786139893171
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A Supervised Learning Approach for Criminal Identification : Using Similarity Measures and K-Medoids Clustering
Published by
LAP LAMBERT Academic Publishing, 2018
ISBN 10: 6139893178
ISBN 13: 9786139893171
New
Taschenbuch
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Data mining tools are best approach for Criminal identification based on characteristic and nature of crime. In this book, we have proposed a supervised approach for identifying the suspected list of criminal's using similarity measure and K-Medoids cluster algorithm. K-Medoids clustering algorithm groups the more closely related crimes as an individual group and each group will have unique set of features. The unique features set is used for identification of criminal using similarity measure algorithms based on distance measure. The proposed system has two phase, training and testing phase. In this approach, we have trained the proposed system with supervised data set with collected crime information from various places of Tamil Nadu through online available data. In the testing phase, first identify the cluster closest to the test crime by using K-Medoids clustering algorithm and then identify the suspected criminal list using similarity measure. The initial stage of implementation and analysis of the proposed scheme provides good results and high accuracy. The proposed scheme is compared with related K-Means clustering algorithm with same set of training and test instances. Seller Inventory # 9786139893171
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A Supervised Learning Approach for Criminal Identification | Using Similarity Measures and K-Medoids Clustering
Published by
LAP LAMBERT Academic Publishing, 2018
ISBN 10: 6139893178
ISBN 13: 9786139893171
New
Taschenbuch
Seller: preigu, Osnabrück, Germany
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Taschenbuch. Condition: Neu. A Supervised Learning Approach for Criminal Identification | Using Similarity Measures and K-Medoids Clustering | Indrani Balasundaram | Taschenbuch | 56 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9786139893171 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Seller Inventory # 114639561