A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf
.
A Hybrid Reduction Approach for Enhancing Cancer Classification of Microarray Data
2014
International Journal of Advanced Research in Artificial Intelligence (IJARAI)
This paper presents a novel hybrid machine learning (ML)reduction approach to enhance cancer classification accuracy of microarray data based on two ML gene ranking techniques (T-test and Class Separability (CS)). The proposed approach is integrated with two ML classifiers; Knearest neighbor (KNN) and support vector machine (SVM); for mining microarray gene expression profiles. Four public cancer microarray databases are used for evaluating the proposed approach and successfully accomplish the
doi:10.14569/ijarai.2014.031001
fatcat:v2ar5qeswjcpzhcpal2q3sg2ei