Research Poster

Knowledge discovery in databases (KDD) is a process which consists of multiple contiguous steps, done iteratively to find knowledge from very large datasets. The data-mining step of knowledge discovery is computationally time consuming , if we work with very large databases. Clustering is one form of unsupervised learning in machine learning techniques used for data mining. Here, a Meta learning approach is taken by me that is used to scale supervised learning, to scale unsupervised learning. This approach uses a number of clustering algorithms to be performed for the base classification systems and then it learns relationships among the base classification systems to achieve final predictions. The base classifiers can be executed on independent computers to perform not only processor scaling, but data scaling also.Read less