Visual Studio Magazine

K-Means Data Clustering from Scratch Using C#

K-means is comparatively simple and works well with large datasets, but it assumes clusters are circular/spherical in shape, so it can only find simple cluster geometries. Data clustering is the ...
Semiconductor Engineering

Spark On AWS Graviton2 Best Practices: K-Means Clustering Case Study

This report focuses on how to tune a Spark application to run on a cluster of instances. We define the concepts for the cluster/Spark parameters, and explain how to configure them given a specific set ...
Visual Studio Magazine

Clustering Mixed Categorical and Numeric Data Using k-Means with C#

Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on a "very tricky" machine learning technique. Data clustering is the process of grouping data items together so ...

Fuleisi Launches Patent for Big Data-Based Intelligent Registration Management System to Enhance Hospital Operational Efficiency

In the wave of medical technology innovation in 2025, Henan Fuleisi Technology Co., Ltd. has submitted a patent application titled "An Intelligent Registration Management System Based on Big Data," ...
JSTOR Daily

k-POD: A Method for k-Means Clustering of Missing Data

The k-means algorithm is often used in clustering applications but its usage requires a complete data matrix. Missing data, however, are common in many applications. Mainstream approaches to ...