Classification of Incomplete Data Handling Techniques - An Overview
Data mining, the extraction of hidden predictive information from large databases, is a technology with great potential that predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions. It is a multidisciplinary field, drawing work from areas including database technology, artificial intelligence, machine learning, neural networks, statistics, pattern recognition, knowledge-based systems, knowledge acquisition, information retrieval, high-performance computing and data visualization. The task of classification with incomplete data is a complex phenomena and its performance depends upon the method selected for handling the missing data. Missing data occur in datasets when no data value is stored for an attribute/feature in the dataset.