The Statistical Learning &
Prediction Modelling Research Group
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In statistics the prime focus is usually in understanding the data and relationships in terms of models by estimating parameters and quantifying uncertainty of these estimates. Machine learning uses computer-intensivelearning-algorithms and focus on prediction and classification and less on mechanisms. Statistical learning theory tries to unify the two approaches and thus studies within a statistical framework the properties of learning algorithms commonly used in machine learning.
The Statistical Learning & Prediction Modelling Group is a research group within the Department of Biostatistics and Health Informatics at the Institute of Psychiatry, Psychology and Neuroscience headed by Daniel Stahl (Email: daniel.r.stahl@kcl.ac.uk). Our research focus is to combine machine learning methods from computer science and statistical models (which make probabilistic assumptions about the underlying phenomena) to improve the development of methods in gaining knowledge, making predictions or decisions and constructing models from a set of data. We are particular interested in developing and applying new statistical learning methods to develop prediction models of treatment success (Personalized or stratified medicine) and future outcomes (Prognosis).
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In psychiatry, statistical learning and prediction modelling provides many methodological challenges including unbalanced groups, population substructure, multi-centre trials, missing data, multicollinearity or validating predictive models. Furthermore, trials databases can contain different measures of the same underlying construct and therefore calibration methods need to be developed before the identification of predictors can proceed. The Statistical Learning and Prediction modelling group meets every third Wednesday of the month at 4pm in the Peter Lantos room (M2.17, second floor, main building, IoPPN) to discuss ongoing projects, problems and questions or to introduce new methods. People who are interested in joining the seminars should contact Daniel Stahl (mail: daniel.r.stahl@kcl.ac.uk).
Furthermore, Dr. Raquel Iniesta organizes a machine learning journal club, which takes place at the first Wednesday of a month at 4pm (SGDP building). People who are interested in joining the seminars should contact her (mail: raquel.iniesta@kcl.ac.uk)
