Name
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. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1145/2393216.2393229 | CCSEIT |
Keywords | Field | DocType |
different clustering algorithm,discretization technique,selected survey,different discretization technique,different classification technique,gene functional prediction,clustering algorithm,discretized gene expression data,preprocessing task,computational construction,gene expression data analysis,discretization | Discretization,Data mining,Computer science,Preprocessor,Artificial intelligence,Cluster analysis,Machine learning | Conference |
Citations | PageRank | References |
3 | 0.38 | 9 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Priyakshi Mahanta | 1 | 32 | 2.87 |
| Hasin Afzal Ahmed | 2 | 55 | 5.65 |
| Jugal K. Kalita | 3 | 856 | 62.32 |
| Dhruba K. Bhattacharyya | 4 | 226 | 27.72 |