Microarray Classification of Cancerous Cell Using Soft Computing Technique

In the late 19th century, the advent of malignant tissues in the human cells has come into limelight. A lot of research works has been carried out to detect the tumorous cells and subsequently, various methodologies have been adopted to distinguish different types of cancerous cells. Gene expression based microarray technique has been used as an efficient and emerging technique in the field of cancer classification, prediction, diagnosis and many other type of research. In this paper,we have used Microarray data which is a collection of microscopic spots. Since there is an existence of huge dataset, the dimensionality reduction of the dataset is done at the first stage of our work. At the second stage, classification is performed using supervised learning methods. At the final stage, we have optimized the objective function using soft computing technique which yields the relevant results.Soft computing refers to a consortium of computational methodologies that has motivated many scientific researchers to contribute their efforts in designing highly powerful intelligent systems. We are mainly focusing on the classification of cancerous cells using two classifiers called SVM (support vector machine) and K-NN (K-nearest neighbor) and an optimization technique is being incorporated on significant parameters that results in better and relevant output.