High dimensionality refers to the presence of a large number of features or variables in a dataset, making it complex and challenging to analyze. In contexts like text and web mining, high dimensionality often arises from the vast number of unique words, phrases, or web features that can be extracted from textual data, leading to issues such as sparsity and difficulty in model training. This complexity can impact the effectiveness of machine learning algorithms and necessitates the use of dimensionality reduction techniques to simplify the data for better analysis and insight extraction.
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