Preprocessing and Classification Algorithms on Micro Array Data for Cancer Classification

Cancer is most dangerous disease and most of the deaths are because of this deadly disease. Microarray cancer analysis is currently one of the most popular study topics in machine learning, computational biology. In the case of binary classes, classification and analysis of cancer data play a critical role in diagnosis, distinguishing negative and positive cases and treatment. The curse of dimensionality and a lack of sufficient sample data are the key challenges with microarray cancer datasets. In this paper presents, problems associated with micro array and handling of problems and make datasets ready for analysis. Different classification algorithms explained with pros and cons of each algorithm in detail.