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| Article Name : | | | METRIC SPACES IN MACHINE LEARNING: DISTANCE FUNCTIONS AND ALGORITHMIC IMPLICATIONS | | Author Name : | | | Dr. Anant Nivruttirao Patil | | Publisher : | | | Ashok Yakkaldevi | | Article Series No. : | | | ROR-15890 | | Article : | |  | Author Profile | | Abstract : | | | In many machine learning (ML) applications, especially in the fields of distance functions and algorithmic analysis, the study of metric spaces is essential. A set in which the distance between any two points is defined by a distance function, often known as a metric, is called a metric space. Many machine learning algorithms depend on this framework, especially those that use clustering, classification, and anomaly detection, where the concept of distance plays a key role in decision-making. | | Keywords : | | - Metric spaces, ,distance functions,
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