Introduction

Beymani consists of set of Hadoop and storm based tools for outlier and anamoly detection, which can be used for fraud detection.

Philosophy

• Simple to use
• Input output in CSV format
• Metadata defined in simple JSON file
• Extremely configurable with tons of configuration knobs

Blogs

The following blogs of mine are good source of details of beymani

• http://pkghosh.wordpress.com/2012/01/02/fraudsters-outliers-and-big-data-2/
• http://pkghosh.wordpress.com/2012/02/18/fraudsters-are-not-model-citizens/
• http://pkghosh.wordpress.com/2012/06/18/its-a-lonely-life-for-outliers/
• http://pkghosh.wordpress.com/2012/10/18/relative-density-and-outliers/
• http://pkghosh.wordpress.com/2013/10/21/real-time-fraud-detection-with-sequence-mining/

Algorithms

• Multi variate distribution model
• Average Distance
• Relative Density
• Markov chain

Getting started

Project's resource directory has various tutorial documents for the use cases described in the blogs.

Help

Please feel free to email me at [email protected]