This repository contains the collection of UCI (real-life) datasets and Synthetic (artificial) datasets (with cluster labels and MATLAB files) ready to use with clustering algorithms.

Data Mining project : Built a classifier, trained a classifier, created clusters, performed 5-fold-cross-validation.

Cluster labelling was done by using the power of wikipedia search

A KNIME-based machine learning workflow for psychographic customer segmentation using the K-Means clustering algorithm. This project analyzes survey-based consumer behavior data, groups similar customers into clusters, and generates cluster labels and centroid summaries to support marketing analytics, customer profiling,and business decision-making