What is a problem with high-dimensional data?

What is a problem with high-dimensional data?



The curse of dimensionality, or the Hughes effect.As the feature space's dimensionality increases, more training data is required to ensure that there are enough training instances with each combination of the feature's values. If there are insufficient training instances for a feature, the algorithm may overfit noise in the training data and fail to generalize.

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