Aug 24, 2003 · This summarization provides insights into the composition of potential classifiers. We present here algorithms and methods for mining a high ...
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We present in this paper the problem of discovering sets of attribute-value pairs in high dimensional data sets that.
This summarization provides insights into the composition of potential classifiers. We present here algorithms and methods for mining a high dimensional data ...
In this chapter, we present several state-of-art techniques for analyzing high-dimensional data, e.g., frequent pattern mining, clustering, and classification.
In this chapter, we present several state-of-art techniques for analyzing high-dimensional data, e.g., frequent pattern mining, clustering, and classification.
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High-dimensional data mining. This section discusses several modern high-dimensional data mining methods recently proposed for molecular genetic applications.
Feb 12, 2010 · My answer: nothing. SVMs are designed to handle high-dimensional data. I'm working on a research problem right now that involves supervised ...
In this chapter, we present several state-of-art techniques for analyzing high- dimensional data, e.g., frequent pattern mining, clustering, and classification.
Nov 24, 2021 · Mining useful knowledge from high-dimensional data is a hot research topic. Efficient and effective sample classification and feature ...
High-dimensional datasets and colossal patterns in data mining involve the discovery of significant patterns in datasets with a large number of features.
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