Reconstruction of a Complete Dataset from an Incomplete Dataset by PCA (Principal Component Analysis) Technique: Some Results
Sameer S. Prabhune, Shri Sant · 2010
Many data analysis applications such as data mining web mining, information retrieval system, require various forms of data preparation. Mostly all this works on the assumption that the data they work is complete in nature, but that is not true! In data preparation, one takes the data in its raw form, removes as much as noise, redundancy and incompleteness as possible and brings out that core for further processing. Indeed, data preparation often presents a less glamorous but in fact a most critical step than other in data analysis applications. It is a data processing technique such that minor data quality adjustments may lead to wrong interpretation that deteriorates the overall effectiveness of any techniques (viz. Data Mining). The input to any algorithm for interpretation is assumed a nice data distribution, containing no missing, inconsistent or incorrect values. But in real world databases, information is missing,