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PhyloM: A Computer Program for Phylogenetic Inference from Measurement or Binary Data, with Bootstrapping [PDF]
Life, 2022 Quantitative and binary results are ubiquitous in biology. Inasmuch as an underlying genetic basis for the observed variation in these observations can be assumed, it is pertinent to infer the evolutionary relationships among the entities being measured.
Sudhindra R. Gadagkar
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Hierarchical Classification using Binary Data
AI Magazine, 2018 In classification problems, especially those that categorize data into a large number of classes, the classes often naturally follow a hierarchical structure. That is, some classes are likely to share similar structures and features.
Molitor, Denali, Needell, Deanna
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Discovering Human Activities from Binary Data in Smart Homes. [PDF]
Sensors (Basel), 2020 With the rapid development in sensing technology, data mining, and machine learning fields for human health monitoring, it became possible to enable monitoring of personal motion and vital signs in a manner that minimizes the disruption of an individual ...
Eldib M, Philips W, Aghajan H.
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Binary Classification with Imbalanced Data
Entropy, 2023 When the binary response variable contains an excess of zero counts, the data are imbalanced. Imbalanced data cause trouble for binary classification. To simplify the numerical computation to obtain the maximum likelihood estimators of the zero-inflated ...
Jyun-You Chiang +4 more
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LASSO type penalized spline regression for binary data [PDF]
BMC Medical Research Methodology, 2021 Background Generalized linear mixed models (GLMMs), typically used for analyzing correlated data, can also be used for smoothing by considering the knot coefficients from a regression spline as random effects.
Muhammad Abu Shadeque Mullah +2 more
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Logistic Biplot by Conjugate Gradient Algorithms and Iterated SVD
Mathematics, 2021 Multivariate binary data are increasingly frequent in practice. Although some adaptations of principal component analysis are used to reduce dimensionality for this kind of data, none of them provide a simultaneous representation of rows and columns ...
Jose Giovany Babativa-Márquez +1 more
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A Markov Chain Monte Carlo Algorithm for Spatial Segmentation
Information, 2021 Spatial data are very often heterogeneous, which indicates that there may not be a unique simple statistical model describing the data. To overcome this issue, the data can be segmented into a number of homogeneous regions (or domains). Identifying these
Nishanthi Raveendran, Georgy Sofronov
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BMC Psychology, 2022 Background The COVID-19 remains a public health burden that has caused global economic crises, jeopardizing health, jobs, and livelihoods of millions of people around the globe.
Naznin Sultana +11 more
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GEOSPATIAL DATA EXCHANGE USING BINARY DATA SERIALIZATION APPROACHES [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 In this paper we investigate the benefits of binary data serialization as a means of storing and sharing large amounts of geospatial data in an interoperable way.
P. Mooney, M. Minghini
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Partial Least Squares Regression for Binary Responses and Its Associated Biplot Representation
Mathematics, 2022 In this paper, we propose a generalization of Partial Least Squares Regression (PLS-R) for a matrix of several binary responses and a a set of numerical predictors. We call the method Partial Least Squares Binary Logistic Regression (PLS-BLR).
Laura Vicente-Gonzalez +1 more
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