A microarray gene expressions with classification using extreme learning machine

M. Yasodha, P. Ponmuthuramalingam
<span title="">2015</span> <i title="National Library of Serbia"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/rjfovdqegrcg3c3vm3udwtsnbm" style="color: black;">Genetika</a> </i> &nbsp;
M. and P. Ponmuthuramalingam (2015): A microarray gene expressions with classification using extreme learning machine. Vol 47, No. 2,[523][524][525][526][527][528][529][530][531][532][533][534] In the present scenario, one of the dangerous disease is cancer. It spreads through blood or lymph to other location of the body, it is a set of cells display uncontrolled growth, attack and destroy nearby tissues, and occasionally metastasis. In cancer diagnosis and molecular biology, a utilized
more &raquo; ... e tool is DNA microarrays. The dominance of this technique is recognized, so several open doubt arise regarding proper examination of microarray data. In the field of medical sciences, multicategory cancer classification plays very important role. The need for cancer classification has become essential because the number of cancer sufferers is increasing. In this research work, to overcome problems of multicategory cancer classification an improved Extreme Learning Machine (ELM) classifier is used. It rectify problems faced by iterative learning methods such as local minima, improper learning rate and over fitting and the training completes with high speed.
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