Knowledge discovery in biological big data using near unsupervised learning: Keynote presentation

Unsupervised learning is used for analysing and clustering data when the expected cluster labels are completely absent. When a little knowledge about the data labels, i.e., class labels are scarce, but available for a small amount of data, it is still challenging to make conclusions, although this may be the case for many real world data mining problems. This type of learning algorithms useful in this scenario as Near Unsupervised Learning (NUL).The concept and the algorithm development is discuss in NUL and the application in various biological data mining problems.