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   Articles with "mixed data" as a keyword



Multipartition clustering of mixed data with Bayesian networks

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recommendations! Published in 2022 at "International Journal of Intelligent Systems"

DOI: 10.1002/int.22770

Abstract: Real‐world applications often involve multifaceted data with several reasonable interpretations. To cluster this data, we need methods that are able to produce multiple clustering solutions. To this purpose, it is interesting to learn a finite… read more here.

Keywords: clustering mixed; data bayesian; bayesian networks; mixed data ... See more keywords

Detecting bias in abundance estimates of spawning fish from closed‐capture models using remote and physical capture data

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recommendations! Published in 2024 at "North American Journal of Fisheries Management"

DOI: 10.1002/nafm.11031

Abstract: Mixed‐data models incorporating remote antenna detections from PIT‐tagged fish together with physical capture data (mixed data) can improve precision of mark–recapture abundance estimates, particularly for spawning fish. However, if the entire population is not available… read more here.

Keywords: abundance; mixed data; abundance estimates; physical capture ... See more keywords

PretopoMD: pretopology-based mixed data hierarchical clustering

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recommendations! Published in 2025 at "Applied Intelligence"

DOI: 10.1007/s10489-025-06770-1

Abstract: This article presents a novel pretopology-based algorithm designed to address the challenges of clustering mixed data without the need for dimensionality reduction. Leveraging Disjunctive Normal Form, our approach formulates customizable logical rules and adjustable hyperparameters… read more here.

Keywords: mixed data; data hierarchical; pretopology based; pretopomd pretopology ... See more keywords
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A novel DBSCAN with entropy and probability for mixed data

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recommendations! Published in 2017 at "Cluster Computing"

DOI: 10.1007/s10586-017-0818-3

Abstract: In big data situation, to detect clusters of different size and shape is a challenging and imperative task. Density based clustering approaches have been widely used in many areas of science due to its simplicity… read more here.

Keywords: entropy probability; dbscan entropy; novel dbscan; mixed data ... See more keywords

Mixed data sampling expectile regression with applications to measuring financial risk

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recommendations! Published in 2020 at "Economic Modelling"

DOI: 10.1016/j.econmod.2020.06.018

Abstract: Abstract To avoid information loss or measurement error in traditional methods dealing with mixed frequency data, we develop a novel mixed data sampling expectile regression (MIDAS-ER) model to measure financial risk. We construct the MIDAS-ER… read more here.

Keywords: data sampling; risk; mixed data; expectile regression ... See more keywords
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Inverse eigenvalue problems for a damped Stieltjes string with mixed data

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recommendations! Published in 2020 at "Linear Algebra and its Applications"

DOI: 10.1016/j.laa.2020.04.023

Abstract: Abstract In this paper, we consider the inverse eigenvalue problem for a Stieltjes string subject to the Robin condition at the left end and a damping condition at the right end with mixed data, which… read more here.

Keywords: inverse eigenvalue; stieltjes string; mixed data; eigenvalue problems ... See more keywords

High-dimensional mixed data sampling models with a covariate-dependent threshold

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recommendations! Published in 2025 at "Econometric Reviews"

DOI: 10.1080/07474938.2025.2481471

Abstract: Abstract. This article introduces high-dimensional mixed data sampling models with a covariate-dependent threshold, which allows for a threshold effect in the relationship between dependent and independent variables sampled at different frequencies and allows for threshold… read more here.

Keywords: mixed data; data sampling; dimensional mixed; high dimensional ... See more keywords

An Advanced Hybrid Logistic Regression Model for Static and Dynamic Mixed Data Classification

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recommendations! Published in 2022 at "IEEE Access"

DOI: 10.1109/access.2022.3187767

Abstract: We consider the binary classification problem of static and dynamic mixed data in this paper. Different from mixed categorical and numerical data, the dynamic variables in the new type of data vary with time and… read more here.

Keywords: classification; hybrid logistic; mixed data; model ... See more keywords

Mixed Data Imputation Using Generative Adversarial Networks

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recommendations! Published in 2022 at "IEEE Access"

DOI: 10.1109/access.2022.3218067

Abstract: Missing values are common in real-world datasets and pose a significant challenge to the performance of statistical and machine learning models. Generally, missing values are imputed using statistical methods, such as the mean, median, mode,… read more here.

Keywords: training data; machine learning; generative adversarial; mixed data ... See more keywords

Achieving Efficient Privacy-Preserving Mixed Data Quality Assessment in Mobile Crowdsensing

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recommendations! Published in 2025 at "IEEE Internet of Things Journal"

DOI: 10.1109/jiot.2024.3481263

Abstract: In mobile crowdsensing (MCS) applications, the single type data is inadequate to reflect the complexities of the real world and meet precise task requirements. Currently, there are few works that focus on mixed data in… read more here.

Keywords: quality; mixed data; privacy; data quality ... See more keywords

Layer-Specific Optimization for Mixed Data Flow With Mixed Precision in FPGA Design for CNN-Based Object Detectors

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recommendations! Published in 2021 at "IEEE Transactions on Circuits and Systems for Video Technology"

DOI: 10.1109/tcsvt.2020.3020569

Abstract: Convolutional neural networks (CNNs) require both intensive computation and frequent memory access, which lead to a low processing speed and large power dissipation. Although the characteristics of the different layers in a CNN are frequently… read more here.

Keywords: layer specific; mixed precision; data flow; chip ... See more keywords