High dimensionality refers to a scenario in data analysis where the number of features or variables in a dataset is very large, often exceeding the number of observations. This situation can complicate the analysis, as it can lead to challenges like overfitting and the curse of dimensionality, which impacts the performance of machine learning algorithms, especially in the context of processing terahertz imaging data.
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