curse of dimensionality

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“Many data mining tools are hard to solve when the number of dimensions or attributes is large. Clustering with K-means and association analysis are two main examples, but similar problems arise with most tools. Often, the only solution is to reduce the number of dimensions; such as examining purchases by categories (such as soda and crackers) instead of detailed items (such as Coke, Diet Coke, Pepsi, and so on). “

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By |February 1st, 2019|Comments Off on curse of dimensionality