The goal of the paper is to present the framework for combining clustering and classification for churn management in … approach to churn management using clustering and classification, which was tested on the churn dataset with a rich variable …

proximity based on almost 600,000 individual transactions. The findings indicate that significant clustering occurs in time and … across industries, while the results on geographic clustering are mixed. This supports the view that merger waves are mostly …

, monetary model for engineering features that quantify investor behaviours, and unsupervised machine learning clustering …

We introduce unFEAR, Unsupervised Feature Extraction Clustering, to identify economic crisis regimes. Given labeled …