Selecting which explanatory variables to include in a given score is a common difficulty, as a balance must be found between statistical fit and practical application. This article presents a methodology for construct...Selecting which explanatory variables to include in a given score is a common difficulty, as a balance must be found between statistical fit and practical application. This article presents a methodology for constructing parsimonious event risk scores combining a stepwise selection of variables with ensemble scores obtained by aggregation of several scores, using several classifiers, bootstrap samples and various modalities of random selection of variables. Selection methods based on a probabilistic model can be used to achieve a stepwise selection for a given classifier such as logistic regression, but not directly for an ensemble classifier constructed by aggregation of several classifiers. Three selection methods are proposed in this framework, two involving a backward selection of the variables based on their coefficients in an ensemble score and the third involving a forward selection of the variables maximizing the AUC. The stepwise selection allows constructing a succession of scores, with the practitioner able to choose which score best fits his needs. These three methods are compared in an application to construct parsimonious short-term event risk scores in chronic HF patients, using as event the composite endpoint of death or hospitalization for worsening HF within 180 days of a visit. Focusing on the fastest method, four scores are constructed, yielding out-of-bag AUCs ranging from 0.81 (26 variables) to 0.76 (2 variables).展开更多
The present aim is to update, upon arrival of new learning data, the parameters of a score constructed with an ensemble method involving linear discriminant analysis and logistic regression in an online setting, witho...The present aim is to update, upon arrival of new learning data, the parameters of a score constructed with an ensemble method involving linear discriminant analysis and logistic regression in an online setting, without the need to store all of the previously obtained data. Poisson bootstrap and stochastic approximation processes were used with online standardized data to avoid numerical explosions, the convergence of which has been established theoretically. This empirical convergence of online ensemble scores to a reference “batch” score was studied on five different datasets from which data streams were simulated, comparing six different processes to construct the online scores. For each score, 50 replications using a total of 10N observations (N being the size of the dataset) were performed to assess the convergence and the stability of the method, computing the mean and standard deviation of a convergence criterion. A complementary study using 100N observations was also performed. All tested processes on all datasets converged after N iterations, except for one process on one dataset. The best processes were averaged processes using online standardized data and a piecewise constant step-size.展开更多
Let W be a real symplectic space and(G,G')an irreducible dual pair in Sp(W),in the sense of Howe,with G compact.Let G be the preimage of G in the metaplectic group Sp(W).Given an irreducible unitary representation...Let W be a real symplectic space and(G,G')an irreducible dual pair in Sp(W),in the sense of Howe,with G compact.Let G be the preimage of G in the metaplectic group Sp(W).Given an irreducible unitary representation II of G that occurs in the restriction of the Weil representation to G,let On denote its character.We prove that,for a suitable embedding T of Sp(W)in the space of tempered distributions on W,the distribution T(On)admits an asymptotic limit,and the limit is a nilpotent orbital integral.As an application,we compute the wave front set of II',the representation of G dual to II,by elementary means.展开更多
We are concerned, in a static regime, with a three-dimensional bounded domain of certain an imaging approach of the locations in electromagnetic imperfections. This approach is related to Electrical Impedance Tomograp...We are concerned, in a static regime, with a three-dimensional bounded domain of certain an imaging approach of the locations in electromagnetic imperfections. This approach is related to Electrical Impedance Tomography and makes use of a new perturbation formula in the electric fields. We present two localization procedures, from a Current Pro- jection method that deals with the single imperfection context and an inverse Fourier process that is devoted to multiple imperfections configurations. These procedures extend those that were described in our previous work, since operating for a broader class of settings. Namely, the localization is additionally performed for certain purely electric imperfections, as established from numerical simulations.展开更多
In this paper,we consider the first order Hardy inequalities using simple equalities.This basic setting not only permits to derive quickly many well-known Hardy inequalities with optimal constants,but also supplies im...In this paper,we consider the first order Hardy inequalities using simple equalities.This basic setting not only permits to derive quickly many well-known Hardy inequalities with optimal constants,but also supplies improved or new estimates in miscellaneous situations,such as multipolar potential,the exponential weight,hyperbolic space,Heisenberg group,the edge Laplacian,or the Grushin type operator.展开更多
文摘Selecting which explanatory variables to include in a given score is a common difficulty, as a balance must be found between statistical fit and practical application. This article presents a methodology for constructing parsimonious event risk scores combining a stepwise selection of variables with ensemble scores obtained by aggregation of several scores, using several classifiers, bootstrap samples and various modalities of random selection of variables. Selection methods based on a probabilistic model can be used to achieve a stepwise selection for a given classifier such as logistic regression, but not directly for an ensemble classifier constructed by aggregation of several classifiers. Three selection methods are proposed in this framework, two involving a backward selection of the variables based on their coefficients in an ensemble score and the third involving a forward selection of the variables maximizing the AUC. The stepwise selection allows constructing a succession of scores, with the practitioner able to choose which score best fits his needs. These three methods are compared in an application to construct parsimonious short-term event risk scores in chronic HF patients, using as event the composite endpoint of death or hospitalization for worsening HF within 180 days of a visit. Focusing on the fastest method, four scores are constructed, yielding out-of-bag AUCs ranging from 0.81 (26 variables) to 0.76 (2 variables).
文摘The present aim is to update, upon arrival of new learning data, the parameters of a score constructed with an ensemble method involving linear discriminant analysis and logistic regression in an online setting, without the need to store all of the previously obtained data. Poisson bootstrap and stochastic approximation processes were used with online standardized data to avoid numerical explosions, the convergence of which has been established theoretically. This empirical convergence of online ensemble scores to a reference “batch” score was studied on five different datasets from which data streams were simulated, comparing six different processes to construct the online scores. For each score, 50 replications using a total of 10N observations (N being the size of the dataset) were performed to assess the convergence and the stability of the method, computing the mean and standard deviation of a convergence criterion. A complementary study using 100N observations was also performed. All tested processes on all datasets converged after N iterations, except for one process on one dataset. The best processes were averaged processes using online standardized data and a piecewise constant step-size.
基金the University of Oklahoma for hospitality and financial supporthospitality and financial support from the Université de Lorraine+1 种基金partial support from NSA (Grant No. H98230-13-1-0205)NSF (Grant No. DMS-2225892)
文摘Let W be a real symplectic space and(G,G')an irreducible dual pair in Sp(W),in the sense of Howe,with G compact.Let G be the preimage of G in the metaplectic group Sp(W).Given an irreducible unitary representation II of G that occurs in the restriction of the Weil representation to G,let On denote its character.We prove that,for a suitable embedding T of Sp(W)in the space of tempered distributions on W,the distribution T(On)admits an asymptotic limit,and the limit is a nilpotent orbital integral.As an application,we compute the wave front set of II',the representation of G dual to II,by elementary means.
文摘We are concerned, in a static regime, with a three-dimensional bounded domain of certain an imaging approach of the locations in electromagnetic imperfections. This approach is related to Electrical Impedance Tomography and makes use of a new perturbation formula in the electric fields. We present two localization procedures, from a Current Pro- jection method that deals with the single imperfection context and an inverse Fourier process that is devoted to multiple imperfections configurations. These procedures extend those that were described in our previous work, since operating for a broader class of settings. Namely, the localization is additionally performed for certain purely electric imperfections, as established from numerical simulations.
基金supported by the Science and Technology Commission of Shanghai Municipality(STCSM)(Grant No.18dz2271000)X.Huang is partially supported by the NSFC(Grant No.11971169).
文摘In this paper,we consider the first order Hardy inequalities using simple equalities.This basic setting not only permits to derive quickly many well-known Hardy inequalities with optimal constants,but also supplies improved or new estimates in miscellaneous situations,such as multipolar potential,the exponential weight,hyperbolic space,Heisenberg group,the edge Laplacian,or the Grushin type operator.
