An Effective Pre-Processing Phase for Gene Expression Classification

Choon Sen Seah (Universiti Tun Hussein Onn Malaysia)
Shahreen Kasim (Universiti Tun Hussein Onn Malaysia)
Mohd Farhan Md Fudzee (Universiti Tun Hussein Onn Malaysia)
Mohd Saberi Mohamad (Universiti Malaysia Kelantan)
Rd Rohmat Saedudin (Telkom University)
Rohayanti Hassan (Universiti Teknologi Malaysia)
Mohd Arfian Ismail (Universiti Teknologi Malaysia)
Rodziah Atan (University Putra Malaysia)

Indonesian Journal of Electrical Engineering and Computer Science
Vol 11, No 3: September 2018

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.