Missing Data Imputation, Classification and Clustering

While performing data analysis the data must be complete. Unfortunately, the problem analysts face is that they are not able to get complete data - perhaps data is missing. Many mechanisms are there to deal with incomplete data. In this book, hybrid techniques were discussed to find out the missing data and to impute the values. For imputation, hybrid techniques were introduced. The classification and clustering been considered and implemented using optimization based neural networks concepts.

Autorentext
Rajalingam, RajaniI am Dr. Rajani Rajalingam working as a Head & Professor in the department of Computer Science and Engineering, Ravindra College of Engineering for Women. My areas of interest include Machine Learning, Deep Learning, Artificial Intelligence, Data Mining and Computer Networks, etc.