Results 71 to 80 of about 4,692,865 (188)
MissForest—non-parametric missing value imputation for mixed-type data [PDF]
, 2017 Motivation: Modern data acquisition based on high-throughput technology is often facing the problem of missing data. Algorithms commonly used in the analysis of such large-scale data often depend on a complete set.
Bühlmann, Peter, Stekhoven, Daniel J.
core
Double exchange mechanisms for Mn doped III-V ferromagnetic semiconductors
, 2003 A microscopic model of indirect exchange interaction between transition metal impurities in dilute magnetic semiconductors (DMS) is proposed. The hybridization of the impurity d-electrons with the heavy hole band states is largely responsible for the ...
Fleurov, V. +4 more
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, 2018 Equilibrium magnetic properties of the mixed state in type-II superconductors were measured with high purity bulk and film niobium samples in parallel and perpendicular magnetic fields using dc magnetometry and scanning Hall-probe microscopy. Equilibrium
Bending, S. +7 more
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StatsThis paper describes a region-oriented method of pattern classification based on the Cartesian system model (CSM), a mathematical model that allows manipulating mixed feature-type symbolic data. We use the supervised hierarchical conceptual clustering to
Manabu Ichino, Hiroyuki Yaguchi
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Mixed-Mode: Past, Present, and Future
Survey Research Methods, 2018 Mixed-mode surveys have been around since the late 1980s. In the past thirty years, major changes in technology and society influenced and changed data collection and survey methodology. However, in those years, mixed-mode strategies remained part of the
Edith D. DeLeeuw
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Issues with rounding in the GCC implementation of the ISO 18037:2008 standard fixed-point arithmetic
, 2020 We describe various issues caused by the lack of round-to-nearest mode in the \textit{gcc} compiler implementation of the fixed-point arithmetic data types and operations.
Mikaitis, Mantas
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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.
Cortese F., Pievatolo A.
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Optimal error estimates of a mixed finite element method for\ud parabolic integro-differential equations with non smooth initial data [PDF]
, 2010 In this article, a new mixed method is proposed and analyzed for parabolic integro-differential equations (PIDE) with nonsmooth initial data. Compared to mixed methods for PIDE, the present method does not bank on a reformulation using a resolvent ...
Goswami, D., Pani, A. K., Yadav, S
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Type-I superconductivity in noncentrosymmetric superconductor AuBe
, 2019 The noncentrosymmetric superconductor AuBe have been investigated using the magnetization, resistivity, specific heat, and muon-spin relaxation/rotation measurements.
Hillier, A. D., Singh, D., Singh, R. P.
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IEEE AccessUnsupervised feature selection (UFS) for mixed-type data is challenging because there are no labels, and traditional methods cannot handle heterogeneous feature spaces effectively.
Hasta Pratama +2 more
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