R Language in Data Mining Techniques and Statistics

Abstract

Data mining is a set of techniques and methods relating to the extraction of knowledge from large amounts of data (through automatic or semi-automatic methods) and further scientific, industrial or operational use of that knowledge. Data mining is closely related to the statistics as an applied mathematical discipline with an analysis of data that could be defined as the extraction of useful information from data.The only difference between the two disciplines is that data mining is a new discipline that is related to significant or large data sets. R is an object-oriented programming language. This means that everything what is done with R can be saved as an object. Every object has a class. It describes what the object contains and what each function does. Application of R as a programming language and statistical software is much more than a supplement to Stata, SAS, and SPSS. Although it is more difficult to learn, the biggest advantage of R is its free-of-charge feature and the wealth of specialized application packages and libraries for a huge number of statistical, mathematical and other methods. R is a simple, but very powerful data mining and statistical data processing tool and once "discovered", it provides users with an entirely new, rich and powerful tool applicable in almost every field of research.