Comparative Study of J48, ADTree, REPTree and BFTree Data Mining Algorithms through Colon Tumour Dataset

The Weka workbench is a designed set of state-of-the-art machine learning techniques and data pre-processing tools. The primary way of relating with these methods is by calling up them from the command line. However, suitable interactive graphical user interfaces are provided for data exploration, for setting up large-scale test on distributed computing platforms. Classification is a significant data mining technique with major applications. It classifies data of different kinds. Decision Trees are a mixture of tree predictors such that every tree depends on the values of a random vector sampled independently and with the same distribution for all trees in the forest. This paper has been carried out to make a performance evaluation of J48, ADTree, REPTree and BFTree classification algorithm. For processing Weka API were used. The data set from the UCI Machine learning Repository is used in this experiment.