Processing Of Incomplete Data Set
Mahesh Shelke, K.B. Badade · IJCER · 2013
A large number of Data Sets are available, but they are incomplete in nature so that they cannot be used for real applications. These incomplete data sets are produced due to various reasons like system failure, privacy of data, incomplete input, time delay in system, lack of available resources. As common examples Weather data sets, sensor image data sets, Measurement Reflection in Agriculture Data Sets. For these cases we use conceptual data reconstruction by using statistical models of multiple linear Regressions to Predict Missing values in Data Sets.