FAACOSE: A Fast Adaptive Ant Colony Optimization Algorithm for Detecting SNP Epistasis by Lin Yuan, Chang-An Yuan, De-Shuang Huang

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Long Short-Term Memory Recurrent Neural Network for Predicting the Return of Rate Underframe the Fama-French 5 Factor by Bui Thanh Khoa, Tran Trong Huynh

“…This study applied a machine learning technique to compare the performance of the Fama-French 5-factor model (FF5). …”
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Analisis Kredit Pembayaran Biaya Kuliah Dengan Pendekatan Pembelajaran Mesin by Arliyanti Nurdin, Rizqa Amelia Zunaidi, Muhammad Arkan Fauzan Wicaksono, Agi Lobita Japtara Martadinata

“…Pada penelitian ini, algoritma machine learning digunakan untuk analisis kredit pembayaran biaya kuliah pada perguruan tinggi. …”
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Enhancing Sentiment Analysis with a CNN-Stacked LSTM Hybrid Model by Shao Shuaijie

“…The performance of the model can be further improved, offering valuable insights for future hybrid model development in machine learning tasks.…”
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Diabetes Risk Assessment: A Comparative Study of Decision Trees and Ensemble Learning Models by Lei Tianxing

“…This high accuracy highlights the effectiveness of machine learning algorithms in predicting diabetes risk. …”
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Bulk Handling Facility Modeling and Simulation for Safeguards Analysis by Benjamin B. Cipiti, Nathan Shoman

“…This paper will describe the SSPM and its use for applying both traditional nuclear material accountancy and newer machine learning options.…”
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Online Supervised Learning with Distributed Features over Multiagent System by Xibin An, Bing He, Chen Hu, Bingqi Liu

“…Most current online distributed machine learning algorithms have been studied in a data-parallel architecture among agents in networks. …”
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A Hybrid Swarm Intelligence Algorithm for Intrusion Detection Using Significant Features by P. Amudha, S. Karthik, S. Sivakumari

“…To investigate the performance of the proposed method, intrusion detection KDDCup’99 benchmark dataset from the UCI Machine Learning repository is used. The performance of the proposed method is compared with the other machine learning algorithms and found to be significantly different.…”
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A Support Vector Machine Model with Hyperparameters Optimised by Mind Evolutionary Algorithm for Assessing Permeability of Rock by Wenjin Zhu, Zhiming Chao, Guotao Ma

“…MEA can increase the predictive accuracy of the constructed machine learning models remarkably in a few iteration times, which has better optimisation performance than that of GA and PSO. …”
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Deep Learning- and Word Embedding-Based Heterogeneous Classifier Ensembles for Text Classification by Zeynep H. Kilimci, Selim Akyokus

“…The ensemble of base classifiers includes traditional machine learning algorithms such as naïve Bayes, support vector machine, and random forest and a deep learning-based conventional network classifier. …”
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Multidisciplinary ML Techniques on Gesture Recognition for People with Disabilities in a Smart Home Environment by Christos Panagiotou, Evanthia Faliagka, Christos P. Antonopoulos, Nikolaos Voros

“…In this paper, three methods for gesture recognition and computer vision were implemented and tested in order to investigate the most suitable one. All methods, machine learning using IMU, machine learning on device, and were combined with certain activities that were determined during a needs analysis research. …”
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Addressing Label Noise in Colorectal Cancer Classification Using Cross-Entropy Loss and pLOF Methods With Stacking-Ensemble Technique by Ishrat Zahan Tani, Kah Ong Michael Goh, Md Nazmul Islam, Md Tarek Aziz, S. M. Hasan Mahmud, Dip Nandi

“…Early diagnosis of this disease is of utmost importance to increase the survival rate and enhance the healthcare system. Many machine learning (ML) and deep learning (DL) methods have been proposed to facilitate automated early diagnosis of this cancer. …”
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Study on Intelligent Classing of Public Welfare Forestland in Kunyu City by Meng Sha, Hua Yang, Jianwei Wu, Jianning Qi

“…This study proposes an innovative machine learning-based approach to forestland classification, utilizing a Support Vector Machine (SVM) model to automate the classification process and enhance both efficiency and accuracy. …”
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Integrating Information Gain and Chi-Square for Enhanced Malware Detection Performance by Fauzi Adi Rafrastara, Wildanil Ghozi, Ramadhan Rakhmat Sani, Lekso Budi Handoko, Abdussalam Abdussalam, Elkaf Rahmawan Pramudya, Faizal M. Abdollah

“…Recent studies have shown that this challenge can be addressed by employing machine learning algorithms for detection. Some studies have also implemented various feature selection methods to optimize detection efficiency. …”
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Enhanced Disc Herniation Classification Using Grey Wolf Optimization Based on Hybrid Feature Extraction and Deep Learning Methods by Yasemin Sarı, Nesrin Aydın Atasoy

“…Finally, the optimized feature set is fed into machine learning classifiers (MLP and SVM) for classification. …”
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Hybridization of DEBOHID with ENN algorithm for highly imbalanced datasets by Sedat Korkmaz

“…Machine learning algorithms assume that datasets are balanced, but most of the datasets in the real world are imbalanced. …”
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Developing multifactorial dementia prediction models using clinical variables from cohorts in the US and Australia by Caitlin A. Finney, David A. Brown, Artur Shvetcov

“…This study used machine learning to re-examine the diagnostic potential of clinical measures for dementia. …”
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Enhancing Artificial Intelligence on a Real Mobile Game by Fabio Aiolli, Claudio E. Palazzi

“…We studied a simple and computationally light machine learning method that can be employed with success, enabling AI improvements for imperfect information games even on mobile phones. …”
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A systematic assessment of sentiment analysis models on iraqi dialect-based texts by Hafedh Hameed Hussein, Amir Lakizadeh

“…These models were evaluated against various machine learning and deep learning models. For feature extraction, we utilized Continuous Bag of Words (CBOW) for deep learning models and BERT for the AraBERT model, while TF-IDF was used for machine learning models. …”
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Fusion-Learning-Based Optimization: A Modified Metaheuristic Method for Lightweight High-Performance Concrete Design by Ghodrat Rahchamani, Seyed Mojtaba Movahedifar, Amin Honarbakhsh

“…It is possible to accurately predict the quality of concrete and the amount of raw materials used using machine learning-enhanced methods. An automated process based on machine learning strategies is proposed in this paper for predicting the compressive strength of concrete. …”
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