imagmiss: Visualization of Missing Data

In dprep: Data Pre-Processing and Visualization Functions for Classification

Description

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.

Author(s)

Caroline Rodriguez and Edgar Acuna

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.

Examples

#---- Plotting datasets with missing values
data(hepatitis)
imagmiss(hepatitis, "hepatitis")

dprep documentation built on May 29, 2017, 11:01 a.m.