A LITERATURE REVIEW ON THE USE OF GENETIC ALGORITHMS IN DATA MINING

Increased globalization and competition have also increased the need for useful knowledge. The development of technology around the world has increased the data storage capacity. However, it is necessary to obtain useful information from the growing data sets. Data mining is one of the methods used to reach a useful information. Data mining allows to take out useful and confidential data from large quantities of data and it can be done as quickly as possible. At this point, data mining techniques which are capable of handling large amounts of data quickly and accurately are also important. Genetic algorithms work in the direction of the principle of survival of the best. In a genetic algorithm, a population of candidate solutions (called individuals, creatures, or phenotypes) to an optimization problem is evolved toward better solutions. In this study, it was explained the importance and definition of data mining, relationships with other disciplines of data mining, data mining models and techniques used in data mining. By examining genetic algorithms which are a data mining method; description and qualifications of genetic algorithms, working principles and their contributions are mentioned. By examining genetic algorithms which are a data mining method; description and qualifications of genetic algorithms, working principles and mentioned of contributions to data mining. The use of genetic algorithm techniques in the field of data mining has been examined. The contribution of the genetic algorithm technique to data mining has been investigated with the literature examples examined and it is aimed to exemplify the usage methods which may be advantageous.