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- W2022928211 abstract "Discretization techniques are widely used as preprocessing task in different classification techniques specially in the area of machine learning. These techniques have also been used as a preprocessing task for computational construction of regulatory networks in gene expression data analysis. We analyze the use of some widely used discretization techniques in other gene expression data analysis tasks such as gene functional prediction. This paper evaluates the performance of these discretization techniques as a preprocessing task by applying the discretized gene expression data on different clustering algorithms. The results generated by the clustering algorithms are internally and externally validated against different discretization techniques. Finally, we introduce some of the important issues and research challenges." @default.
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- W2022928211 date "2012-10-26" @default.
- W2022928211 modified "2023-10-16" @default.
- W2022928211 title "Discretization in gene expression data analysis" @default.
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- W2022928211 doi "https://doi.org/10.1145/2393216.2393229" @default.
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