Clustering is a common data mining technique that groups similar data points together based on some criteria. It can be used for various purposes, such as exploratory analysis, customer ...

When you create a query against a data mining model, you can retrieve metadata about the model, or create a content query that provides details about the patterns discovered in analysis. Alternatively ...

The first step in sharing your data mining and clustering expertise is to know your audience and their needs, expectations, and preferences. Depending on who you are addressing, you may need to ...

Clustering, a component of data mining is the process of grouping objects into several clusters such that objects in the same cluster have maximum similarity while the objects in different clusters ...

Specialization: Data Mining Foundations and Practice Instructor: Dr. Qin (Christine) Lv, Associate Professor of Computer Science Prior knowledge needed: Familiarity of functionalities in Python, basic ...

Clustering categorical attributes is an important task in data mining; however, it has not received much attention. Some of the popular algorithms, such as ROCK, COOLCAT, and CACTUS, are described. An ...

Remote sensing data plays a key role in understanding the complex geographic phenomena. Clustering is a useful tool in discovering interesting patterns and structures within the multivariate ...

A practical approach to data mining with large volumes of complex data; prepare, cleanse and explore data; supervised and unsupervised modelling with association rules and market basket analysis, ...