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 ...

The k-value at that point is often a good choice. This is called the "elbow" technique. An alternative for clustering mixed categorical and numeric data is to use an old technique called k-prototypes ...

For example, K-Means clustering algorithm in machine learning is a compute-intensive algorithm, while Word Count is more memory intensive. For this report, we explore tuning parameters to run K-Means ...

Tableaus’ new drag and drop clustering function, for example, automatically finds patterns in data using a k-means function. A user can call the clustering function by simply dragging it from the ...

Clustering algorithms are a powerful form of AI that can be applied to business challenges from customer segmentation to fraud detection.

With the influx of data and self-service analytics tools, we're going to need more people capable of communicating insights effectively. The next generation of data storytellers will not be ...