implementing data mining algorithms (3 résultats)

Paperback. Etat : Brand New. 80 pages. 8.66x5.91x0.19 inches. In Stock.

Taschenbuch. Etat : Neu. Electronic Banking Fraud Detection | Using Data Mining Techniques And R Software For Implementing Machine Learning Algorithms In Prevention Of Fraud | Sayo Enoch Aluko | Taschenbuch | 80 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9783659916878 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This research work deals with the procedures for computing the presence of outliers using various distance measures and general detection performance for unsupervised machine learning, such as the K-Mean Clustering Analysis and Principal Component Analysis. A comprehensive evaluation of Data Mining Techniques, Machine Learning and Predictive modelling for Unsupervised Anomaly Detection Algorithms on Electronic Banking Transaction data sets record for over a period of six (6) months, April to September, 2015, consisting of 9 variable data fields and 8,641 observations, were used to carry out the survey on fraud detection. On completion of the underlying system, I can conclude that integrated techniques system provide better performance efficiency than a singular system. Besides, in near real-time settings, if a faster computation is required for larger data sets, just like the unlabelled data sets used for this research work, clustering based method is preferred to classification model.