This article presents a technique for clustering mixed categorical and numeric data using standard k-means clustering implemented using the C# language. Briefly, the source mixed data is preprocessed ...

K-medoids: This is similar to the k-means, but the center is calculated using a median algorithm. Fuzzy : Each point can be a member of multiple clusters that are calculated using any type of ...

K-means is a commonly used algorithm in machine learning. It is an unsupervised learning algorithm. It is regularly used for data clustering. Only the number of clusters are needed to be specified for ...

K-means clustering is an unsupervised learning algorithm, and out of all the unsupervised learning algorithms, K-means clustering might be the most widely used, thanks to its power and simplicity. How ...

Data clustering, or cluster analysis, is the process of grouping data items so that similar items belong to the same group/cluster. There are many clustering techniques. In this article I'll explain ...