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The "curse of dimensionality" is a term used to describe various phenomena that arise when analyzing and organizing data in high-dimensional spaces that do not occur in low-dimensional settings. It is particularly relevant in fields like statistics, machine learning, and data analysis. Here are several key aspects of the curse of dimensionality: 1. **Sparsity of Data**: In high-dimensional spaces, data points tend to be sparse.

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