Silhouettes: a graphical aid to the interpretation and validation of cluster analysis
Journal of Computational and Applied Mathematics
On Clustering Validation Techniques
Journal of Intelligent Information Systems
On Changing Continuous Attributes into Ordered Discrete Attributes
EWSL '91 Proceedings of the European Working Session on Machine Learning
Center CLICK: A Clustering Algorithm with Applications to Gene Expression Analysis
Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology
A Time Series Analysis of Microarray Data
BIBE '04 Proceedings of the 4th IEEE Symposium on Bioinformatics and Bioengineering
IEEE Transactions on Pattern Analysis and Machine Intelligence
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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.