Evolutionary_data_mining
Evolutionary data mining, or genetic data mining is an umbrella term for any data mining using evolutionary algorithms. While it can be used for mining data from DNA sequences,[1] it is not limited to biological contexts and can be used in any classification-based prediction scenario, which helps "predict the value ... of a user-specified goal attribute based on the values of other attributes."[2] For instance, a banking institution might want to predict whether a customer's credit would be "good" or "bad" based on their age, income and current savings.[2] Evolutionary algorithms for data mining work by creating a series of random rules to be checked against a training dataset.[3] The rules which most closely fit the data are selected and are mutated.[3] The process is iterated many times and eventually, a rule will arise that approaches 100% similarity with the training data.[2] This rule is then checked against a test dataset, which was previously invisible to the genetic algorithm.[2]