Missing Values and Optimal Selection of an Imputation Method and Classification Algorithm to Improve the Accuracy of Ubiquitous Computing Applications

Table 3

Imputation methods.

Imputation methods	Description
Listwise deletion	Perhaps the most basic traditional technique for dealing with missing data. Cases with missing values are discarded, restricting the analyses to cases for which complete data are available.
Mean imputation	Involves replacing missing data with the overall mean for the observed data.
Group mean imputation	A missing value is replaced by the mean of a subset of the data, based on other observed variable(s) in the data.
Predictive mean imputation	Also called regression imputation. Predictive mean imputation involves imputing a missing value using an ordinary least-squares regression method to estimate missing data.
Hot-deck	Most similar records are imputed to missing values.
-NN	The attribute value of is imputed to the most similar instance from nonmissing data.
-means clustering	numbers of sets are created that are homogeneous on the inside and heterogeneous on the outside.