The descriptives of a PCB Footprint Library helps you organize, simplify and understand the underlying information of a large data set. They allow you to work on a set of data organized in variable instances in which none of the individual variables is of particular importance in relation to others. They are used for example to clear, a set of individuals, homogeneous groups.
In addition to typology to build standards of behavior and thus deviations from these standards, such as the detection of new or unknown to credit card fraud. And, to make the information compression or image compression possible, etc.
Among the techniques available, those from statistics can be exploited. They are grouped under the term factor analysis, statistical methods to identify information hidden in a variables, these hidden variables are called factors. In the factor analysis, it is assumed that if the data is dependent on them.
