7.4 Mining High-Dimensional Data and Colossal Patterns

The frequent pattern mining methods presented so far handle large data sets having a small number of dimensions. However, some applications may need to mine high-dimensional data (i.e., data with hundreds or thousands of dimensions). Can we use the methods studied so far to mine high-dimensional data? The answer is unfortunately negative because the search spaces of such typical methods grow exponentially with the number of dimensions.

Researchers have overcome this difficulty in two directions. One direction extends a pattern growth approach by further exploring the vertical data format to handle data sets with a large number of dimensions (also called features or items, e.g., genes) but ...

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