Visual Studio Magazine

K-Means Data Clustering Using C#

Data clustering is the process of placing data items into groups so that items within a group are similar and items in different groups are dissimilar. The most common technique for clustering numeric ...
JSTOR Daily

A k -mean-directions Algorithm for Fast Clustering of Data on the Sphere

A k-means-type algorithm is proposed for efficiently clustering data constrained to lie on the surface of a p-dimensional unit sphere, or data that are mean-zero-unit-variance standardized ...
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 ...
TechRepublic

Implementation of an Entropy Weighted K-Means Algorithm for High Dimensional Sparse Data

In this paper, the authors contain a partitional based algorithm for clustering high-dimensional objects in subspaces for iris gene dataset. In high dimensional data, clusters of objects often exist ...
Visual Studio Magazine

K-Means Data Clustering Using C#

Data clustering is the process of placing data items into groups so that items within a group are similar and items in different groups are dissimilar. The most common technique for clustering numeric ...