Embedded feature selection can be performed by analyzing the variables used in a Random Forest. Such a multivariate selection takes into account the interactions between variables but is not straightforward to interpret in a statistical sense. We propose a statistical procedure to measure variable importance that tests if variables are significantly useful in combination with others in a forest...

Community structure is one of the main structural features of networks, revealing both their internal organization and the similarity of their elementary units. Despite the large variety of methods proposed to detect communities in graphs, there is a big need for multi-purpose techniques, able to handle different types of datasets and the subtleties of community structure. In this paper we pres...

Testing the out-of-sample forecasting superiority of one model over another requires an a priori partitioning of the data into a model specification /estimation (‘training’) period and a model comparison/evaluation (‘out-of-sample’ or ‘validation’) period. How large a validation period is necessary for a given mean square forecasting error (MSFE) improvement to be statistically significant at t...

Knowledge of the association information between the attributes in a data set provides insight into the underlying structure of the data and explains the relationships (independence, synergy, redundancy) between the attributes. Complex models learnt computationally from the data are more interpretable to a human analyst when such interdependencies are known. In this paper, we focus on mining tw...

In the questionnaire analysis, finding whether there is a statistically significant difference between two or more groups in a continuous measure is one of the major problems in researches. However, it is difficult for researchers to solve the issue of finding possible statistically significant difference, namely “Statistically Significant Difference Unawareness Issue”. There are two causes to ...

Vision programming is deened as the task of constructing explicit object models to be used in object recognition. These object models specify the features to be used in recognizing the object as well as the exact order in which they have to be used. For 3D recognition, in the absence of grouping information, the number of bases (model feature/image feature correspondences) that must be examined...

Remote sensing, medical imaging, and time-lapse seismic monitoring have common challenges in change detection. In this paper we introduce a statistical procedure developed in medical imaging to determine if anomalies in time-lapse seismic data are statistically significant. Using seismic data redundancy, we construct maps of statistical variation and apply an adaptive thresholding to them. The ...

MOTIVATION The regulatory machinery controlling gene expression is complex, frequently requiring multiple, simultaneous DNA-protein interactions. The rate at which a gene is transcribed may depend upon the presence or absence of a collection of transcription factors bound to the DNA near the gene. Locating transcription factor binding sites in genomic DNA is difficult because the individual sit...