A Classification Model Based on Interval Rule Inference Network with Interpretability by Yunxia Zhang, Yiming Zhong, Xiaochang Wu, Jing Bai

“…Interpretability requirements, complex uncertain data processing, and limited training data are characteristics of classification in some real industry applications. The interval belief rule base (IBRB) can deal with various types of uncertainty and provides high interpretability. …”
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Enhanced framework for ensemble effort estimation by using recursive‐based classification by Azath Hussain, Maheswari Raja, Pandimurugan Vellaisamy, Sangeetha Krishnan, Lakshminarayanan Rajendran

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Stationary solutions to a hybrid viscous hydrodynamic model with classical boundaries by Federica Di Michele, Bruno Rubino, Rosella Sampalmieri, Kateryna Stiepanova

“…In this paper we present a quantum-classical hybrid model based on the hydrodynamic equations in steady state form. …”
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Spatial Cognitive EEG Feature Extraction and Classification Based on MSSECNN and PCMI by Xianglong Wan, Yue Sun, Yiduo Yao, Wan Zuha Wan Hasan, Dong Wen

“…This study proposes a novel approach for EEG signal classification, utilizing Permutation Conditional Mutual Information (PCMI) for feature extraction and a Multi-Scale Squeezed Excitation Convolutional Neural Network (MSSECNN) model for classification. …”
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Zero-BertXGB: An Empirical Technique for Abstract Classification in Systematic Reviews by Mohammad Shariful Islam, Mohammad Abu Tareq Rony, Md Rasel Hossain, Samah Alshathri, Walid El-Shafai

Subjects: “…Abstract classification…”
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A Novel Multimode Fault Classification Method Based on Deep Learning by Funa Zhou, Yulin Gao, Chenglin Wen

“…In the second hierarchy , different DNN classification models are constructed for each mode to get more accurate fault classification result. …”
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Crime Prediction Using Decision Tree (J48) Classification Algorithm. by Ivan, Niyonzima, Emmanuel Ahishakiye, Elisha Opiyo Omulo, Danison Taremwa

Subjects: “…crime prediction; machine learning; decision tree; J48; artificial intelligence; Classification Algorithms.…”
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Deep Learning Techniques in DICOM Files Classification: A Systematic Review by Mabirizi, Vicent, Kawuma, Simon, Natumanya, Deborah, Wasswa, William

“…Guided by Arksey and O’Malley’s scoping methodology, the review reveals that existing deep learning techniques typically rely on converting DICOM images into simpler formats like JPEG, TIF, or PNG for classification, a process that often results in metadata loss and reduced classification accuracy. …”
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An ensemble machine learning-based performance evaluation identifies top In-Silico pathogenicity prediction methods that best classify driver mutations in cancer by Subrata Das, Vatsal Patel, Shouvik Chakravarty, Arnab Ghosh, Anirban Mukhopadhyay, Nidhan K. Biswas

“…Methods The study used a dataset from 502 HNSC patients, classifying mutations based on 299 known high-confidence cancer driver genes. …”
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Fake News Detection and Classification: A Comparative Study of Convolutional Neural Networks, Large Language Models, and Natural Language Processing Models by Konstantinos I. Roumeliotis, Nikolaos D. Tselikas, Dimitrios K. Nasiopoulos

Subjects: “…fake news classification…”
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Resistify: A Novel NLR Classifier That Reveals Helitron-Associated NLR Expansion in Solanaceae by Moray Smith, John T Jones, Ingo Hein

“…Resistify is an easy-to-use, rapid, and accurate tool to identify and classify NLRs from protein sequences. Applying Resistify to the RefPlantNLR database demonstrates that it can correctly identify NLRs from a diverse range of species. …”
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To Predict the Requirement of Pharmacotherapy by OGTT Glucose Levels in Women with GDM Classified by the IADPSG Criteria by Gülen Yerlikaya, Veronica Falcone, Tina Stopp, Martina Mittlböck, Andrea Tura, Peter Husslein, Wolfgang Eppel, Christian S. Göbl

“…The aim of this study was to assess the association between OGTT glucose levels and requirement of pharmacotherapy in GDM patients classified by the IADPSG criteria. This study included 203 GDM patients (108 managed with lifestyle modification and 95 requiring pharmacotherapy). …”
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A Fusion Parameter Method for Classifying Freshness of Fish Based on Electrochemical Impedance Spectroscopy by Jian Sun, Yuhao Liu, Gangshan Wu, Yecheng Zhang, Rongbiao Zhang, X. J. Li

“…Compared with using a single characteristic parameter of electrochemical impedance spectroscopy (EIS) to classify the freshness of fish samples from different origins, more characteristic parameters could bring higher accuracy as well as complexity, subjectivity, and uncertainty. …”
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Credit Risk Evaluation with a Least Squares Fuzzy Support Vector Machines Classifier by Lean Yu

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Farmer’s Credit Rating Model and Application Based on Multilayer Unified Network with Linear Classifier by Sulin Pang, Shouyang Wang, Lianhu Xia

“…In order to solve the problem of farmers' credit rating, this paper also designs a linear segmentation classifier to classify the results of multilayer unidirectional network, establishes the rules of farmers' credit rating and the unidirectional network linear segmentation evaluation model of farmers' credit rating, and discusses the properties of bank credit based on farmers’ credit rating. …”
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Characterisation of the Aerodynamic Aerosol Classifier Transfer Function for Particle Sizes up to 5 Micrometres by Simon D. Payne, Tyler J. Johnson, Jonathan P. R. Symonds

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Postface. Postérités du cinéma classique hollywoodien dans les remontages expérimentaux contemporains by Marie-Pierre Burquier

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Copy-Move Forgery Verification in Images Using Local Feature Extractors and Optimized Classifiers by S. B. G. Tilak Babu, Ch Srinivasa Rao

“…The proposed algorithms can classify an image efficiently as either copy-move forged or authenticated, even if the test image is subjected to attacks such as JPEG compression, scaling, rotation, and brightness variation. …”
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A Multiple-Classifier Framework for Parkinson’s Disease Detection Based on Various Vocal Tests by Mahnaz Behroozi, Ashkan Sami

“…As a solution, we introduced a new framework that applies an independent classifier for each vocal test. The final classification result would be a majority vote from all of the classifiers. …”
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A Closest Resemblance Classifier with Feature Interval Learning and Outranking Measures for Improved Performance by Nabil Belacel

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