Anomaly, also known as outlier, is a set of data points that are considerably different than the remainder of the data. Unlike to the noise, detection of anomalies in data set is very important as anomalies may lead to a catastrophic outcomes in a real life because they are important factors on misleading the learners. The objective with the outlier detection is to find all data points in a given data set x D with anomaly scores greater than some threshold t. Visual, statistical, distance-based, density based, and clustering-based approaches are often applied for detection of the outliers.