A Comparison of Data Mining Classification Algorithms Using Breast Cancer Microarray Dataset: A study

Classification is one of the most familiar data mining Technique and model finding process that is used for transmission the data into different classes according to particular condition. Further the classification is used to forecast group relationship for precise data instance. It is generally construct models that are used to predict potential statistics trends. Medical science industry has huge amount of data, but unfortunately most of this data is not mined to find out hidden information in data, advanced data mining techniques can be used to discover hidden pattern in data. This Present study and analysis of various classification algorithms in data mining. This paper also presents the comparative study on four classification algorithms such as naïve bayes, CART, J48Graft, JRip algorithms using breast cancer dataset. The comparative results show that the J48Graft algorithm gives best classification accuracy than the rest of the algorithms. The algorithms also compared based on the execution time and error rate.