Startup Success Factors: Classifying 3H (Hustler, Hipster, Hacker) Framework using Simple Additive Weighting by Qoriah Indah Susilowati, Fatih Başçiftçi

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TWD-DepNet: a deep network enhanced by three-way decisions for EEG-based depression detection by Chunlei Shi, Shouzhu Yan, Wei He, Haiyan Wang

“…To address these challenges, a novel deep learning framework TWD-DepNet is proposed, which is enhanced by Three-Way Decision (TWD) theory to enable robust EEG-based depression detection. …”
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Data-driven diabetes mellitus prediction and management: a comparative evaluation of decision tree classifier and artificial neural network models along with statistical analysis by Idris Zubairu Sadiq, Babangida Sanusi Katsayal, Bashiru Ibrahim, Maryam Ibrahim, Hassan Aliyu Hassan, Umar Muhammad Ghali, Abdullahi Garba Usman, Abubakar Usman, Sani Isah Abba

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Using a hybrid multi-criteria analysis method to classify hot mix asphalt regarding permanent deformation by Victória Nunes-Ramos, Jéssica da Silva Vieira, Alejandro Ruiz-Padillo, Luciano Pivoto Specht

“…In this sense, multi-criteria decision-making support methodologies can help optimize the mix composition process by simultaneously combining simplified indicators. …”
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Sleep Bruxism Detection Using Decision Tree Method by the Combination of C4-P4 and C4-A1 Channels of Scalp EEG by Md Belal Bin Heyat, Dakun Lai, Faez Iqbal Khan, Yifei Zhang

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Hybrid self-inertia weight adaptive particle swarm optimisation with local search using C4.5 decision tree classifier for feature selection problems by Arfan Ali Nagra, Fei Han, Qing Hua Ling, Muhammad Abubaker, Farooq Ahmad, Sumet Mehta, Abeo Timothy Apasiba

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A Radar-Based System for Detection of Human Fall Utilizing Analog Hardware Architectures of Decision Tree Model by Vassilis Alimisis, Dimitrios G. Arnaoutoglou, Emmanouil Anastasios Serlis, Argyro Kamperi, Konstantinos Metaxas, George A. Kyriacou, Paul P. Sotiriadis

“…The proposed classifier architectures are based on different approximations of the Decision tree classification model. …”
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Decision rule for stratification of patients with chronic heart failure of functional class II and III by E. V. Samoilova, M. A. Fatova, D. R. Mindzaev, I. V. Zhitareva, C. N. Nasonova, I. V. Zhirov, C. N. Tereschenko, A. A. Korotaeva

“…The aim of the study was focused on the development of a decision rule for classifying patients as functional class (FC) II or III of chronic heart failure (CHF) by discriminant analysis with inflammatory markers.Materials and methods. …”
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SNUH methylation classifier for CNS tumors by Kwanghoon Lee, Jaemin Jeon, Jin Woo Park, Suwan Yu, Jae-Kyung Won, Kwangsoo Kim, Chul-Kee Park, Sung-Hye Park

“…We evaluated the performance of three classifiers; SNUH-MC, DKFZ-MC v11b4, and DKFZ-MC v12.5, using specific criteria. …”
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Forecasting: Analyze Online and Offline Learning Mode with Machine Learning Algorithms by Farida Ardiani, Rodhiyah Mardhiyyah, Izaaz Azaam Syahalam, Nasmah Nur Amiroh

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Performance of Machine Learning Classifiers for Diabetes Prediction by Mijala Manandhar, Shaikat Baidya, Babalpreet Kaur, Katia Atoji

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Leveraging federated learning for privacy-preserving analysis of multi-institutional electronic health records in rare disease research by Karthik Meduri, Geeta Sandeep Nadella, Akhila Reddy Yadulla, Vinay Kumar Kasula, Mohan Harish Maturi, Steven Brown, Snehal Satish, Hari Gonaygunta

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An Autism Spectrum Disorder Identification Method Based on 3D-CNN and Segmented Temporal Decision Network by Zhiling Liu, Ye Chen, Xinrui Dong, Jing Liu

“…This study aims to improve the ability to capture spatiotemporal dynamics of brain activity by proposing an advanced framework. (2) Methods: This study proposes an ASD recognition method that combines 3D Convolutional Neural Networks (3D-CNNs) and segmented temporal decision networks. …”
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Calculation Method of Downstream Water Level in Non-Spilling Periods of Hydropower Stations Based on Decision Tree Classification and Multiple Linear Regression by LI Yinghai, HE Liangzhe, ZHANG Hairong, NIE Panpan, QIN Hui, YANG Qingyu, GUO Jiali

“…A multiple linear regression calculation method based on decision tree classification is proposed. This method first employs the classification and regression tree (CART) algorithm, using long-series measured data from hydropower stations to establish decision tree classification rules and classify data of different operation working conditions. …”
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A VIKOR-Based Sequential Three-Way Classification Ranking Method by Wentao Xu, Jin Qian, Yueyang Wu, Shaowei Yan, Yongting Ni, Guangjin Yang

“…However, these improvements and extensions only rank the alternatives without classifying them. For this purpose, this text introduces the three-way sequential decisions method and combines it with the VIKOR method to design a three-way VIKOR method that can deal with both ranking and classification. …”
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The method of rating committee vote algorithms in classification problems with teacher by М. M. Nessonova

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Justifying the selection of a neural network linguistic classifier by Olessia Barkovska, Kseniia Voropaieva, Oleksandr Ruskikh

“…By systematically assessing these attributes, this study aims to provide valuable information about the strengths and weaknesses of each model and enable researchers and practitioners to make informed decisions when selecting a neural network classifier for text classification tasks. …”
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Justifying the selection of a neural network linguistic classifier by Олеся Барковська, Ксенія Воропаєва, Олександр Руських

“…By systematically assessing these attributes, this study aims to provide valuable information about the strengths and weaknesses of each model and enable researchers and practitioners to make informed decisions when selecting a neural network classifier for text classification tasks. …”
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Classifying seismic event parameters using artificial intelligence by Abbas Maazallahi, Kameron Bustos, Mohammad Amir Salari, Eli Snir, Payam Norouzzadeh, Bahareh Rahmani

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Enhancement of Chest X-Ray Images to Improve Screening Accuracy Rate Using Iterated Function System and Multilayer Fractional-Order Machine Learning Classifier by Chia-Hung Lin, Jian-Xing Wu, Chien-Ming Li, Pi-Yun Chen, Neng-Sheng Pai, Ying-Che Kuo

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