Sharif Digital Repository

Classification is one of the most important problems in machine learning area. Reliable and successful classification is essential for diagnosing patients for further treatment. In many applications such as bioinformatics unlabeled data is abundant and available. However labeling data is much more difficult and expensive to obtain. This dissertation presents a novel transductive approach for the development of robust microarray data classification. The transduction problem is to estimate the value of classification function at the given points in the working set. This contrasts with the standard inductive learning problem of estimating the classification method at all possible values and...