Objectives
The objectives of this section are:
to explain the various visualization techniques
to understand in which situation a particular technique is used
to introduce higher dimensional visualization techniques that exist
Outcomes
By the time you have completed this section you will be able to:
choose a visualization technique based on the dataset attribute
create a scatter plot and histogram
Visualization of data with spatial/temporal attributes
The beauty of data presents a problem, by this we refer to the ability for us to gather information about a certain situation in a variety of ways not limited to real numbers that are continuous attributes or even nominal and categorical attributes. We sometimes have data that has spatial or temporal attributes by this we mean that a given data set can consist of a set of observation on a spatial grid and can vary at different points of time. Visualizing these attributes cannot be done with the techniques previously discussed. Contour, surface, and vector field plots are visualization techniques used to visual spatial and temporal attributes.
Visualization of data with many attributes
For a data set that has many attributes, techniques exist to visualize these many dimensions but all of these techniques have limitations of their own that need to be understood so that the proper technique is used to provide us with the aspect of the data that we care the most about. Matrices, Star Coordinates and Parallel Coordinates.
The techniques mentioned in this section are just a few of the visual representations used to display data and their attributes. For more information refer to your traditional data mining course textbook and the intermediate track for this section.
