How can Euclidean distance be implemented in Python?
Euclidean distance is a fundamental concept in machine learning and is widely used in various algorithms such as k-nearest neighbors, clustering, and dimensionality reduction. It measures the straight-line distance between two points in a multidimensional space. In Python, implementing Euclidean distance is relatively straightforward and can be done using basic mathematical operations. To calculate the
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How does K nearest neighbors classify unknown data points?
K nearest neighbors (KNN) is a popular classification algorithm in the field of machine learning. It is a non-parametric and instance-based algorithm that classifies unknown data points based on their proximity to known data points. KNN is a simple yet powerful algorithm that can be easily implemented in Python for classification tasks. To understand how