An effective pre-processing phase for gene expression classification
A raw dataset prepared by researchers comes with a lot of information. Whether the information is usefull or not, completely depends on the requirement and purposes. In machine learning, data pre-processing is the very initial stage. It is a must to make sure the dataset is totally suitable for the...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Institute of Advanced Engineering and Science
2018
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/29329/ http://umpir.ump.edu.my/id/eprint/29329/1/An%20effective%20pre-processing%20phase%20for%20gene%20expression.pdf |
| Summary: | A raw dataset prepared by researchers comes with a lot of information. Whether the information is usefull or not, completely depends on the requirement and purposes. In machine learning, data pre-processing is the very initial stage. It is a must to make sure the dataset is totally suitable for the requirement. In significant directed random walk (sDRW), there are three steps in data pre-processing stage. First, we remove unwanted attributes, missing value and proper arrangement, followed by normalization of the expression value and lastly, filtering method is applied. The first two steps are completed by Bioconductor package while the last step is works in sDRW. |
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