Function to create a graph of the observations of the dataset
leaving white gaps where data is missing.
Usage
imagmiss(data, name = "")
Arguments
data
The dataset containing missing values
name
The name of dataset to be used in title of plot
Details
The main idea is to use the original dataset to create a temporary
dataset containing 1 if a value is found or 0 if the value is missing.
The temporary data set is graphed by column, changing color for each
feature and leaving a blank horizontal line if a value is missing. Assumes
classes are in the last column, and removes the column containing the classes
before plotting. A report that describes the percentage of missing values in the data set
is provided once the visualization is complete.
References
Acuna, E. and Rodriguez, C. (2004). The treatment of missing values and its effect in the classifier accuracy. In D. Banks, L. House, F.R. McMorris, P. Arabie, W. Gaul (Eds).
Classification, Clustering and Data Mining Applications. Springer-Verlag Berlin-Heidelberg, 639-648.