Customer Segmentation of Personal Credit using Recency, Frequency, Monetary (RFM) and K-means on Financial Industry

Segmentation of Photospheric Solar Images by Using c-Means,k-Means, and FCM Algorithms

Discovering Active and Profitable Patterns with Rfm (recency, Frequency and Monetary) Sequential Pattern Mining–a Constraint Based Approach

Sequential pattern mining is an extension of association rule mining that discovers time-related behaviors in sequence database. It extends association by adding time to the transactions. The problem of finding association rules concern with intratransaction patterns whereas that of sequential pattern mining concerns with inter-transaction patterns. Generalized Sequential Pattern (GSP) mining a...

Customer Clustering using RFM analysis

RFM (Recency, Frequency, Monetary) analysis is a method to identify high-response customers in marketing promotions, and to improve overall response rates, which is well known and is widely applied today. Less widely understood is the value of applying RFM scoring to a customer database and measuring customer profitability. RFM analysis is considered significant also for the banks and their spe...

Designing an Algorithm for Cancerous Tissue Segmentation Using Adaptive K-means Cluttering and Discrete Wavelet Transform

Background: Breast cancer is currently one of the leading causes of death among women worldwide. The diagnosis and separation of cancerous tumors in mammographic imagesrequire accuracy, experience and time, and it has always posed itself as a major challenge to the radiologists and physicians. Objective: This paper proposes a new algorithm which draws on discrete wavelet transform and adaptive ...

segmentation of photospheric solar images by using c-means,k-means, and fcm algorithms