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Gaussian Logic for Predictive Classification

Gaussian Logic for Predictive Classification

This video was recorded at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Athens 2011. We describe a statistical relational learning framework called Gaussian Logic capable to work efficiently with combinations of relational and numerical data. The framework assumes that, for a fixed relational structure, the numerical data can be modelled by a multivariate normal distribution. We demonstrate how the Gaussian Logic framework can be applied to predictive classification problems. In experiments, we first show an application of the framework for the prediction of DNAbinding propensity of proteins. Next, we show how the Gaussian Logic framework can be used to find motifs describing highly correlated gene groups in gene-expression data which are then used in a set-level-based classification method.


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