Visualization is the graphic presentation of data-portrayals meant to reveal complex information at a glance, referring to all types of structured representation of information. This includes graphs, charts, diagrams, maps, storyboards, and other structured illustrations.
Good visualization of results gives you the chance to look at data through the eyes of experts. It is beautiful not only for their aesthetic design, but also for the elegant layers of detail that efficiently generate insight and new understanding.
The result of every data mining algorithm can be visualized and clarified by the use of the algorithms. Visualization plays an important role in the data mining process.
There are four major features that create the best visualizations:
- Novel: It must not only merely being a conduit for information, but offer some novelty in the form of new style of information.
- Informative: The attention to these factors and the data itself will make a data visualization effective, successful, and beautiful.
- Efficient: A nice visualization has an explicit goal, a clearly defined message, or a special perspective on the information that it is made to convey. It must be as simple as possible and straightforward, but shouldn't lose out on necessary, relevant complexity. The irrelevant data serves as noises here. It should reflect the qualities of the data that they represent, reveal properties and relationships inherent and implicit in the data source to bring new knowledge, insight, and enjoyment to final user.
- Aesthetic: The graphic must serve the primary goal of presenting information, not only axes and layout, shapes, lines, and typography, but also the appropriate usage of these ingredients.
R provides the production of publication-quality diagrams and plots. There are graphic facilities distributed with R, and also some facilities that are not part of the standard R installation. You can use R graphics from command line.
The most important feature of the R graphics setup is the existence of two distinct graphics systems within R:
- The traditional graphics system
- Grid graphics system
The most appropriate facilities will be evaluated and applied to the visualization of every result of all algorithms listed in the book.
Functions in the graphics systems and add-on packages can be divided into several types:
- High-level functions that produce complete plots
- Low-level functions to add further output to an existing plot
- The ones to work interactively with graphical output
To enhance your knowledge about this chapter, here are some practice questions for you to have check about the concepts.