Results 51 to 60 of about 4,503,666 (319)
Advancing Spectral Clustering for Categorical and Mixed-Type Data: Insights and Applications
MathematicsThis study focuses on adapting spectral clustering, a numeric data-clustering technique, for categorical and mixed-type data. The method enhances spectral clustering for categorical and mixed-type data with novel kernel functions, showing improved ...
Cinzia Di Nuzzo
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Toxoplasma gondii Type I, predominant genotype isolated from sheep in South of Iran [PDF]
Veterinary World, 2017 Aim: This study was performed to determine the genetic diversity of Toxoplasma gondii in sheep using nested-polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) in Southern Iran.
Belal Armand +5 more
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Mathematics, 2023 In this paper, the synchronization problem of uncertain neutral-type neural networks (NTNNs) with sampled-data control is investigated. First, a mixed-delay-dependent augmented Lyapunov–Krasovskii functional (LKF) is proposed, which not only considers ...
Shuoting Wang, Kaibo Shi
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Multivariate Analysis of Mixed Data: The R Package PCAmixdata [PDF]
, 2017 Mixed data arise when observations are described by a mixture of numerical and categorical variables. The R package PCAmixdata extends standard multivariate analysis methods to incorporate this type of data.
Chavent, Marie +3 more
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A comparison of four methods for the analysis of N-of-1 trials. [PDF]
PLoS ONE, 2014 OBJECTIVE: To provide a practical guidance for the analysis of N-of-1 trials by comparing four commonly used models. METHODS: The four models, paired t-test, mixed effects model of difference, mixed effects model and meta-analysis of summary data were ...
Xinlin Chen, Pingyan Chen
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Mathematics, 2021 The distance-based linear model (DB-LM) extends the classical linear regression to the framework of mixed-type predictors or when the only available information is a distance matrix between regressors (as it sometimes happens with big data).
Amparo Baíllo, Aurea Grané
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Cluster Analysis with Balancing Weight on Mixed-type Data
Communications for Statistical Applications and Methods, 2006 A set of clustering algorithms with proper weight on the formulation of distance which extend to mixed numeric and multiple binary values is presented. A simple matching and Jaccard coefficients are used to measure similarity between objects for multiple binary attributes. Similarities are converted to dissimilarities between i th and j th objects. The
Seong S. Chae +2 more
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Clustering of Mixed-Type Data Considering Concept Hierarchies
, 2019 Most clustering algorithms have been designed only for pure numerical or pure categorical data sets while nowadays many applications generate mixed data. It arises the question how to integrate various types of attributes so that one could efficiently group objects without loss of information.
Behzadi, S. +3 more
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Existence of optimal boundary control for the Navier-Stokes equations with mixed boundary conditions [PDF]
, 2015 Variational approaches have been used successfully as a strategy to take advantage from real data measurements. In several applications, this approach gives a means to increase the accuracy of numerical simulations.
Guerra, Telma +2 more
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Methodological Innovations, 2023 Metainferences, or the insights derived from integrating quantitative and qualitative inferences at the end of a study, are crucial for achieving added value and synergy in mixed methods research.
Ahtisham Younas +2 more
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