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Implement the CONCORD algorithm into the HPCC Systems® Machine Learning Library

This project was completed by Syed Rahman. The project was his own idea which he brought to us and completed as a summer intern in 2015. 

The CONCORD algorithm implemented by Syed Rahman

The CONCORD algorithm is a method to estimate the true population of a co-variance matrix. The co-variance matrix is a summary of the relationship between every pair of fields in the data. Co-variance values close to zero indicate that the fields don’t have a relationship. Values close to 1 indicate a positive relationship and values close to –1 indicate an inverse relationship.


For further details please refer to the following JIRA issue for this project.

In 2016, Syed was a returning student intern who completed a machine learning project which is related to this algorithm.