Data Science and Machine Learning (Theory and Projects) A to Z - Feature Selection: Similarity Based Methods Introductio

The video tutorial covers similarity-based methods in feature selection, focusing on both supervised and unsupervised learning. It explains the construction and use of an affinity matrix, which is central to these methods. The tutorial also discusses the role of K-nearest neighbor graphs in defining similarity and introduces the concept of geodesic distance. Applications in feature extraction and future learning modules are briefly mentioned.

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