Classification Of Complex UCI Datasets Using Machine Learning And Evolutionary Algorithms

Abstract Classification is an important data mining technique with broad applications. Classification is a gradual practice for allocating a given piece of input into any of the known category. The Data Mining refers to extracting or mining knowledge from huge volume of data. In this paper different classification techniques of Data Mining are compared using diverse datasets from University of California Irvine UCI Machine Learning Repository. Accuracy and time complexity for execution by each classifier is observed. . Finally different classifiers are also compared with the help of Confusion Matrix. Classification is used to classify each item in a set of data into one of predefined set of classes or groups