János Török (BME)
Thursday 2017-07-27 14.15 – 15.00
Lecture room AS3, TUAS-building
Age prediction using egocentric network
Prediction is often done by supervised learning where the many parameter model (neural network) is trained by the some part of data, and the accuracy of the prediction is then verified on the rest. The problem with these approaches that these systems often behave as a black box and not much can be learned from the results. Here we present a simple model which has basically no adjustable parameter but can predict the age of an ego with 85-90% success rate from the age of its acquaintances, using the egocentric network.