Interaction-Based Learning for High-Dimensional Data with Continuous Predictors
High-dimensional data, such as that relating to gene expression in microarray experiments, may contain substantial amount of useful information to be explored. However, the information, relevant variables and their joint interactions are usually diluted by noise due to a large number of non-informat...
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| Language: | English |
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2014
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| Online Access: | https://doi.org/10.7916/D8X928CH |