• Mrs.M.Porkizhi
• Mrs.S.Nagarathinam

Data mining involves the use of sophisticated data analysis tools to discover previously unknown, valid patterns and relationships in large data sets. Classification is one of the main technique in data mining which will be used to which is the process of verdict a model that describe the data classes or Concepts. These techniques are applied in learning algorithms such as Decision tree (DT), Support Vector Machines (SVM), Naïve Bayes (NB) and Artificial Neural Network (ANN) and these methods can handle both numerical and categorical attributes. This study will be implementing in Rapid Miner tool and it will be applied in Titanic dataset. In this paper, four classification algorithms comparatively test to find the optimum algorithm for this dataset. This study described the performance analysis of classification algorithm based on the correct and incorrect instances of data classification. The comparison will be taking the following parameters such as Precision, Recall, F-Measure, Accuracy and Root mean squared error.

Data mining, Classification, Decision tree, Rapid Miner, Precision, Recall

"EXPLORATION COMPARATIVE OF SUPERVISED LEARNING ALGORITHMS IN CLASSIFICATION MINING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.632-639, June 2019, Available :http://www.jetir.org/papers/JETIR1907235.pdf

"EXPLORATION COMPARATIVE OF SUPERVISED LEARNING ALGORITHMS IN CLASSIFICATION MINING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp632-639, June 2019, Available at : http://www.jetir.org/papers/JETIR1907235.pdf