In recent days, the association analysis is put into practice with legal datasets. The main aim of this research work is to mine association rule from various theft cases collected from different sources within the jurisdiction of State of Tamil Nadu.First, in this thesis it is proposed an innovative Theft Pattern Mining algorithm to mine the frequent item set. The proposed data structure is applied in Theft Pattern Mining algorithm. The performance of the proposed algorithm is compared with the existing Frequent Pattern Mining (FPM) algorithms. The proposed algorithm is comparatively analyzed with the existing U-Apriori, FP-growth and UF-growth algorithms. The performance of the proposed algorithm is studied by using synthetic dataset like T40I10D100K, real dataset like Mushroom, Gazella and the proposed Tamil Nadu Theft Crime (TTC) dataset with special reference to State of Tamil Nadu.
"Sinopsis" puede pertenecer a otra edición de este libro.
Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000. Nº de ref. del artículo: L2-9786209361395
Cantidad disponible: Más de 20 disponibles
Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000. Nº de ref. del artículo: L2-9786209361395
Cantidad disponible: Más de 20 disponibles
Librería: California Books, Miami, FL, Estados Unidos de America
Condición: New. Nº de ref. del artículo: I-9786209361395
Cantidad disponible: Más de 20 disponibles
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 236 pp. Englisch. Nº de ref. del artículo: 9786209361395
Cantidad disponible: 2 disponibles
Librería: CitiRetail, Stevenage, Reino Unido
Paperback. Condición: new. Paperback. In recent days, the association analysis is put into practice with legal datasets. The main aim of this research work is to mine association rule from various theft cases collected from different sources within the jurisdiction of State of Tamil Nadu.First, in this thesis it is proposed an innovative Theft Pattern Mining algorithm to mine the frequent item set. The proposed data structure is applied in Theft Pattern Mining algorithm. The performance of the proposed algorithm is compared with the existing Frequent Pattern Mining (FPM) algorithms. The proposed algorithm is comparatively analyzed with the existing U-Apriori, FP-growth and UF-growth algorithms. The performance of the proposed algorithm is studied by using synthetic dataset like T40I10D100K, real dataset like Mushroom, Gazella and the proposed Tamil Nadu Theft Crime (TTC) dataset with special reference to State of Tamil Nadu. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9786209361395
Cantidad disponible: 1 disponibles
Librería: preigu, Osnabrück, Alemania
Taschenbuch. Condición: Neu. Pattern Analysis from Crime Data | Ramesh kumar K | Taschenbuch | Englisch | 2025 | LAP LAMBERT Academic Publishing | EAN 9786209361395 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. Nº de ref. del artículo: 134442939
Cantidad disponible: 5 disponibles
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In recent days, the association analysis is put into practice with legal datasets. The main aim of this research work is to mine association rule from various theft cases collected from different sources within the jurisdiction of State of Tamil Nadu.First, in this thesis it is proposed an innovative Theft Pattern Mining algorithm to mine the frequent item set. The proposed data structure is applied in Theft Pattern Mining algorithm. The performance of the proposed algorithm is compared with the existing Frequent Pattern Mining (FPM) algorithms. The proposed algorithm is comparatively analyzed with the existing U-Apriori, FP-growth and UF-growth algorithms. The performance of the proposed algorithm is studied by using synthetic dataset like T40I10D100K, real dataset like Mushroom, Gazella and the proposed Tamil Nadu Theft Crime (TTC) dataset with special reference to State of Tamil Nadu.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 236 pp. Englisch. Nº de ref. del artículo: 9786209361395
Cantidad disponible: 1 disponibles
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering. Nº de ref. del artículo: 9786209361395
Cantidad disponible: 1 disponibles
Librería: Books Puddle, New York, NY, Estados Unidos de America
Condición: New. Print on Demand. Nº de ref. del artículo: 26405594876
Cantidad disponible: 4 disponibles
Librería: Majestic Books, Hounslow, Reino Unido
Condición: New. Print on Demand. Nº de ref. del artículo: 408640803
Cantidad disponible: 4 disponibles