Lesson 1 of 4 · 45 min

Data Foundations: Objects, Attributes, and Proximity Measures

Learn how data objects are represented by attributes and how proximity is quantified using common distance measures such as Euclidean, Manhattan, Hamming, and supremum distances, providing the foundation for later mining tasks.

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Lesson explanation

In Introduction to Data Mining (2nd Edition) — Tan, Steinbach, Karpatne, and Kumar, a data set is represented as objects described by attributes. Numeric objects can be viewed as points in an attribute space, and pairwise distances can be organized in a distan...

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