@article{(Open Science Index):https://publications.waset.org/pdf/10000619,
	  title     = {Imputation Technique for Feature Selection in Microarray Data Set},
	  author    = {Younies Mahmoud and  Mai Mabrouk and  Elsayed Sallam},
	  country	= {},
	  institution	= {},
	  abstract     = {Analyzing DNA microarray data sets is a great
challenge, which faces the bioinformaticians due to the complication
of using statistical and machine learning techniques. The challenge
will be doubled if the microarray data sets contain missing data,
which happens regularly because these techniques cannot deal with
missing data. One of the most important data analysis process on
the microarray data set is feature selection. This process finds the
most important genes that affect certain disease. In this paper, we
introduce a technique for imputing the missing data in microarray
data sets while performing feature selection.
	    journal   = {International Journal of Bioengineering and Life Sciences},
	  volume    = {9},
	  number    = {1},
	  year      = {2015},
	  pages     = {306 - 310},
	  ee        = {https://publications.waset.org/pdf/10000619},
	  url   	= {https://publications.waset.org/vol/97},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 97, 2015},