Clustering Customers using Tableau K-Means Algorithm by Sales and Profit Metrics
K-means clustering is a statistical partitioning technique within data science that groups similar high-dimensional data points into distinct clusters based on proximity to mathematical centroids. The core mechanism involves iteratively assigning observations to the nearest centroid and recalculating cluster centers until convergence, operating under the assumption of spherical cluster shapes with uniform variance. This method serves as a fundamental unsupervised learning algorithm used for dimensionality reduction, pattern recognition, and data segmentation within broader fields such as machine learning and exploratory data analysis.
Clustering Customers using Tableau K-Means Algorithm by Sales and Profit Metrics
K-means clustering is a statistical partitioning technique within data science that groups similar high-dimensional data points into distinct clusters based on proximity to mathematical centroids. Th…