K-Means Algorithm, Influenza Transmission, Cluster Analysis, Urban Characteristics Share and Cite: Ye, S. (2025) Application of the K-Means Algorithm in the Study of Influenza Transmission Patterns.

Learn how to cluster your numeric data using the k-means algorithm in this step-by-step guide.

But clustering mixed categorical and numeric data is very tricky. This article presents a technique for clustering mixed categorical and numeric data using standard k-means clustering implemented ...

Overview Understanding key machine learning algorithms is crucial for solving real-world data problems effectively.Data ...

The proposed AFK-MC² method is presented as a simple, yet fast, alternative for k-Means seeding that produces probably good clustering without assumptions on the data.

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 ...

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 ...

Then, you can use clustering results to custom tailor your marketing efforts. In this course, we will explore two popular clustering techniques: Agglomerative hierarchical clustering and K-means ...