Classification and knowledge discovery in protein databases

Classification and knowledge discovery in protein databases

We consider the problem of classification in noisy, high-dimensional, and class-imbalanced protein datasets. In order to design a complete classification system, we use a three-stage machine learning framework consisting of a feature selection stage, a method addressing noise and class-imbalance, and a method for combining biologically related tasks through a prior-knowledge based clustering. I...

Knowledge Discovery in Databases

Knowledge Discovery in Databases

Business information received from advanced data analysis and data mining is a critical success factor for companies wishing to maximize competitive advantage. The use of traditional tools and techniques to discover knowledge is ruthless and does not give the right information at the right time. Knowledge discovery is defined as ``the non-trivial extraction of implicit, unknown, and potentially...

Knowledge Discovery in Databases

Knowledge Discovery in Databases (KDD) is a relatively new field of research. Interest generated by KDD has been huge. International companies are looking to KDD techniques to maximise profit and enhance decision support. The aim of this paper is to provide an overview and understanding of the ideas, techniques and applications found within this field.

Knowledge Discovery from Databases

As databases are pervading every parcel of reality, they record what happens in and around organizations all over the world. Databases store the detailed history of organizations, institutions, governments and individuals. An efficient and agile analysis of the data recorded in a database can no longer be done manually. Knowledge Discovery from Databases (KDD) is a collection of technologies wh...