Results 41 to 50 of about 4,503,666 (319)
Clustering mixed-type data using a probabilistic distance algorithm
Applied Soft Computing, 2022 Cluster analysis is a broadly used unsupervised data analysis technique for finding groups of homogeneous units in a data set. Probabilistic distance clustering adjusted for cluster size (PDQ), discussed in this contribution, falls within the broad category of clustering methods initially developed to deal with continuous data; it has the advantage of ...
Cristina Tortora, Francesco Palumbo
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Statistical jump model for mixed-type data with missing data imputation
Advances in Data Analysis and ClassificationAbstract In this paper, we address the challenge of clustering mixed-type data with temporal evolution by introducing the statistical jump model for mixed-type data. This novel framework incorporates regime persistence, enhancing interpretability and reducing the frequency of state switches, and efficiently handles missing data.
Federico P. Cortese, Antonio Pievatolo
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Differentially private synthetic mixed-type data generation for unsupervised learning [PDF]
Intelligent Decision Technologies, 2021 We introduce the DP-auto-GAN framework for synthetic data generation, which combines the low dimensional representation of autoencoders with the flexibility of Generative Adversarial Networks (GANs). This framework can be used to take in raw sensitive data and privately train a model for generating synthetic data that will satisfy similar statistical ...
Rachel Cummings +4 more
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Improved Estimation of Human Lipoprotein Kinetics with Mixed Effects Models. [PDF]
PLoS ONE, 2015 Mathematical models may help the analysis of biological systems by providing estimates of otherwise un-measurable quantities such as concentrations and fluxes.
Martin Berglund +4 more
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GeV Analysis of Mixed Morphology Supernova Remnants Interacting with Molecular Clouds [PDF]
, 2012 The first remnants detected by the Fermi Gamma-ray Space Telescope were of the type of mixed-morphology supernova remnants interacting with molecular clouds.
Ercan, E. Nihal, Ergin, Tülün
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Sparse semiparametric canonical correlation analysis for data of mixed types [PDF]
Biometrika, 2018 SummaryCanonical correlation analysis investigates linear relationships between two sets of variables, but it often works poorly on modern datasets because of high dimensionality and mixed data types such as continuous, binary and zero-inflated. To overcome these challenges, we propose a semiparametric approach to sparse canonical correlation analysis ...
Grace Yoon +2 more
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Parallel Coordinate Plots of Mixed-Type Data
Communications for Statistical Applications and Methods, 2008 Parallel coordinate plot of Inselberg (1985) is useful for visualizing dozens of variables, but so far the plot’s applicability is limited to the variables of numerical type. The aim of this study is to extend the parallel coordinate plot so that it can accommodate both numerical and categorical variables.
Myung-Hoe Huh, Il Youp Kwak
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BMC Genomics, 2022 Background Mixed models are used to correct for confounding due to population stratification and hidden relatedness in genome-wide association studies. This class of models includes linear mixed models and generalized linear mixed models.
Maryam Onifade +3 more
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Cardiology and Therapy, 2023 Introduction Transthyretin amyloidosis (ATTR amyloidosis) is primarily associated with a cardiac or neurologic phenotype, but a mixed phenotype is increasingly described.
Juan González-Moreno +13 more
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On the mixed Cauchy problem with data on singular conics [PDF]
, 2007 We consider a problem of mixed Cauchy type for certain holomorphic partial differential operators whose principal part $Q_{2p}(D)$ essentially is the (complex) Laplace operator to a power, $\Delta^p$. We pose inital data on a singular conic divisor given
Author(s Ebenfelt +3 more
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