Multipartition clustering of mixed data with Bayesian networks
Sign Up to like & getrecommendations! 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
A novel DBSCAN with entropy and probability for mixed data
Sign Up to like & getrecommendations! 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
Sign Up to like & getrecommendations! 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
Inverse eigenvalue problems for a damped Stieltjes string with mixed data
Sign Up to like & getrecommendations! 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
An Advanced Hybrid Logistic Regression Model for Static and Dynamic Mixed Data Classification
Sign Up to like & getrecommendations! 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
Sign Up to like & getrecommendations! 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
Layer-Specific Optimization for Mixed Data Flow With Mixed Precision in FPGA Design for CNN-Based Object Detectors
Sign Up to like & getrecommendations! 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
Clustering Mixed Data by Fast Search and Find of Density Peaks
Sign Up to like & getrecommendations! Published in 2017 at "Mathematical Problems in Engineering"
DOI: 10.1155/2017/5060842
Abstract: Aiming at the mixed data composed of numerical and categorical attributes, a new unified dissimilarity metric is proposed, and based on that a new clustering algorithm is also proposed. The experiment result shows that this… read more here.
Keywords: search find; find density; fast search; mixed data ... See more keywords
A deep learning mixed-data type approach for the classification of FHR signals
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Bioengineering and Biotechnology"
DOI: 10.3389/fbioe.2022.887549
Abstract: The Cardiotocography (CTG) is a widely diffused monitoring practice, used in Ob-Gyn Clinic to assess the fetal well-being through the analysis of the Fetal Heart Rate (FHR) and the Uterine contraction signals. Due to the… read more here.
Keywords: classification; data type; deep learning; mixed data ... See more keywords
Dynamic Mixed Data Analysis and Visualization
Sign Up to like & getrecommendations! Published in 2022 at "Entropy"
DOI: 10.3390/e24101399
Abstract: One of the consequences of the big data revolution is that data are more heterogeneous than ever. A new challenge appears when mixed-type data sets evolve over time and we are interested in the comparison… read more here.
Keywords: visualization; time; data analysis; analysis visualization ... See more keywords
Waste Management Analysis in Developing Countries through Unsupervised Classification of Mixed Data
Sign Up to like & getrecommendations! Published in 2019 at "Social Sciences"
DOI: 10.3390/socsci8060186
Abstract: The increase in global population and the improvement of living standards in developing countries has resulted in higher solid waste generation. Solid waste management increasingly represents a challenge, but it might also be an opportunity… read more here.
Keywords: analysis; waste; waste management; developing countries ... See more keywords