Knowledge Discovery Using Data mining and Soft Computing Methodologies

Huge amount of data are collected nowadays from different application domains. It is not feasible to analyze all these data manually. Knowledge Discovery in Databases(KDD) is the nontrivial process of identifying valid, novel, potentially useful, and ultimately understandable patterns in data.Valid stands for the discovered patterns (information) should hold for new, previously unseen problem instances to a certain degree.Due to the advances in Computer Science and Information Technology currently it is easy to collect, store and analyze the date. Soft Computing is multidisciplinary field that was proposed by Dr. Lotfi Zadeh, whose goal was to construct new generation Artificial Intelligence, known as Computational Intelligence. The idea of soft computing was initiated in the year 1981 when Dr. Zadeh published his first paper on soft data analysis. This thesis is proposed to be performed for the analysis of data using soft computing models. Initially soft computing has been defined as the fusion of the fields of Fuzzy logic, Neuro computing, Evolutionary and Genetic computing into one multidisciplinary system. In this research work the use of soft computing and statistical models.