Neural network Self Organizing Map
The data warehousing & data mining have changed the decision making process in modern day business environment, which basically equip the business companies to reach their customers with the right product and right offer at the right time. This project is mainly concentrated to analyze the customer churn behavior, fraud detection and customer relationship management (CRM) in a banking system. The project will be implemented with a completely warehouse based business intelligence tools with some of the data mining algorithms implemented during reporting phase for churn prediction and anomaly detection.Since customers usually churn from one company to another quite often and this too is happening at an alarming rate and is becoming the most important issue in customer relationship management, so customer retention is the need of the hour to ponder upon. Our project will implement different visualization methods & techniques through Oracle Business Intelligence tool to analyze churn behavior. For this we will implement classification & regression tree (CART) analysis. The pattern of fraud detection will be implemented as location and time-wise. Rule-based methods such as BAYES, FOIL or RIPPER or Support Vector Machines (SVM) or unsupervised neural network (NN)
Source: CODING EVERYTHING
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