Carlos Rodriguez Calderon

Learning Developer (Mathematics and Statistics, LUMS), PhD (Integrated) student

Research Overview

My interest is to explore a particular machine learning algorithm, a lazy learner, k-Nearest Neighbour (k-NN) as a valid alternative for retail demand forecasting: its advantages regarding classical statistical methods like linear regression and some of its complexities, as the extrapolation scenario and the forecast reliability.


Publication peer-review


Consultancy


Prize (including medals and awards)

  • Centre for Marketing Analytics & Forecasting