MatrixNet is a machine learning algorithm developed by Yandex and widely used in all the company’s products. The algorithm is based on gradient enhancement and has been introduced since 2009.
An important feature of this method is that it is robust to overtraining. This allows very many ranking factors to be taken into account – without increasing the number of assessors’ scores or fearing that the machine will find non-existent patterns.
CERN uses the algorithm to analyse and search the colossal output data generated by the Large Hadron Collider.