RapidMiner Extension: Anomaly Detection

The Anomaly Detection Extension for RapidMiner has been released.

The Anomaly Detection Extension for RapidMiner comprises the most well know unsupervised anomaly detection algorithms, assigning individual anomaly scores to data rows of example sets. It allows you to find data, which is significantly different from the normal, without the need for the data being labeled.

Some of the algorithms are:

• Local Outlier Factor (LOF)
• k-NN Global Anomaly Score
• Connectivity-based Outlier Factor (COF)
• Local Correlation Integral (LOCI)
• Local Outlier Probability (LoOP)
• Cluster-based Local Outlier Factor (CBLOF)