International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE)
Data mining refers to extracting or mining knowledge from large amounts of data. Organizing data into valid groupings is one of the most basic ways of understanding and learning. Cluster analysis is important for analyzing the number of clusters of natural data in several domains. Outlier detection is a fundamental part of data mining. A key challenge with outlier detection is that it is not a well-formulated problem like clustering. This paper discussion on two different techniques and then comparison by analyzing their different accuracy, mean squared error, time complexity.