Advanced Customer Segmentation methods in R
Machine Learning (ML) by using Python
A hybrid optimizer that combines information-theoretic entropy minimization, Bayesian variational updates, and hierarchical clustering to achieve ultra-fast, deterministic convergence on black-box objectives.
A modular pipeline combining a supervised logistic‐regression base model with an unsupervised, two‐level clustering–based anomaly detector.
This report presents a segmentation analysis conducted on a UK bank's customer dataset using hierarchical and two-step clustering techniques. The objective was to identify homogeneous customer groups to support the development of targeted financial products and services.
K-means and hierarchical clustering of GP practices based on QOF performance measures
A study for a UK bank, undertaking segmentation analysis to identify trends and patterns in their customers.
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