The q-factor model adoi:10.2139/ssrn.2520929Hou, KeweiXue, ChenZhang, LuSSRN Electronic JournalHou, K., Xue, C., Zhang, L., 2016. A comparison of new factor models. Ohio State University and the University of Cincinnati working paper....
models.The results fitted by nonrectangular hyperbolic model,rectangular hyperbolic model and the new model were compared.In addition,the measured data of light response of photosynthesis under different temperatures and CO2 concentrations could be dealt with,and the main parameters of photosynthesis,i.e...
1998. A comparison of event models for Na篓ive Bayes text classification. In Proceedings of AAAI/ICML- 98 Workshop on Learning for Text Categorization, ... Y Matsumoto,R Thawonmas - Entertainment Computing-icec, Third International Conference, Eindhoven, the Netherlands, September 被引量: 27发表...
without an in-depth understanding of the epicardium in humans, our ability to translate these models into a therapeutic context is limited. As it stands, it is still not fully known
This article studies the relationship between the two most-used quantile models with endogeneity: the instrumental variable quantile regression (IVQR) model (Chernozhukov and Hansen 2005) and the local quantile treatment effects (LQTE) model (Abadie, Angrist, and Imbens 2002). The key condition of...
Parallel analysis indicated that two factors should be retained (See Table S1 in the online supplements), so four models were examined, including one to two-factor ESEM models, with and without accounting for correlated residual between two reverse-coded items. Of particular note was that the ...
Though many advances have been made in spatiotemporal fusion model development and applications in the past decade, a unified comparison among existing fusion models is still limited. In this research, we classify the models into three categories: transformation-based, reconstruction-based, and ...
While many feature importance methods exist, the explanations obtained with one method may not corroborate with that of another method for the same model [21,35], which can be referred to asexplanation multiplicity. It is known that many different machine learning models can fit data equally well...
Patients at Risk of Readmission: A Comparison of Classification Trees, Logistic Regression, Generalized Additive Models, and Multivariate Adaptive Regression ... Demir - 《Decision》 被引量: 4发表: 2014年 A Review and New Contribution on Conic Multivariate Adaptive Regression Splines (CMARS): A Pow...
23-05-23 DF2M ICML 2024 Deep Functional Factor Models: Forecasting High-Dimensional Functional Time Series via Bayesian Nonparametric Factorization None 24-01-16 STanHop-Net ICLR 2024 STanHop: Sparse Tandem Hopfield Model for Memory-Enhanced Time Series Prediction None 24-02-02 SNN ICML 2024 Effic...