What is "Curse of dimensionality"

In the context of data mining, the curse of dimensionality refers to the fact as the number of features and dimensions in a dataset increases, the amount of data required to accurately represent the distribution of the data increases exponentially, making it difficult to extract useful patterns and relationship from the data.

 

For example, in a dataset with only two features, it may be relatively easy to visualize and identify patterns in the data. However, as the number of features increases, the data becomes more complex and difficult to visualize, making it harder to identify patterns.