A common use of data mining is to detect patterns or rules in data.
The points of interest are the non-obvious patterns that can only be detected using a large dataset. The detection of simpler patterns, such as market basket analysis for purchasing associations or timings, has been possible for some time. Our interest in R programming is in detecting unexpected associations that can lead to new opportunities.
Some patterns are sequential in nature, for example, predicting faults in systems based on past results that are, again, only obvious using large datasets. These will be explored in the next chapter.
This chapter discusses the use of R to discover patterns in datasets' various methods: