Binary Classification of Customer’s Online Purchasing Behavior Using Machine Learning by Ahmad Aldelemy, Raed A. Abd-Alhameed

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RARE: right algorithm for the right errand; a multi-model machine learning-based approach for tourism routes and spots recommendation by Ling Luo

“…This study introduces a novel tourism recommendation system integrating multiple machine learning algorithms to provide personalized tourist spot and route recommendations. …”
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Analysis of Possibilities to Automate Detection of Unscrupulous Microfinance Organizations based on Machine learning Methods by Yu. M. Beketnova

“…The author carried out a comparative analysis of the results obtained by classification methods — the logistic regression method, decision trees (algorithms of two-class decision forest, Adaboost), support vector machine (algorithm of two-class support vector machine), neural network methods (algorithm of two-class neural network), Bayesian networks (algorithm of two-class Bayes network). …”
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Comparative Analysis of a Quantum SVM With an Optimized Kernel Versus Classical SVMs by Matheus Cammarosano Hidalgo

“…Support Vector Machine (SVM) is a widely used algorithm for classification, valued for its flexibility with kernels that effectively handle non-linear problems and high-dimensional data. …”
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Crop yield prediction in agriculture: A comprehensive review of machine learning and deep learning approaches, with insights for future research and sustainability by Md. Abu Jabed, Masrah Azrifah Azmi Murad

“…The research paper also examines the algorithms frequently utilized in the machine learning domain, including Random Forest (RF), Artificial Neural Networks (ANN), and Support Vector Machine (SVM). …”
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Komparasi Algoritma Support Vector Machines dengan Algoritma Artificial Neural Network untuk Memprediksi Nilai Persetujuan Kredit Modal Kerja yang Diberikan Bank Umum by Abu Sopian, Agus Wiyatno, Albert Riyandi

“…Working capital credit approval provided by commercial bank need to predict because it has increased of credit provision provided by commercial bank that can be used as measurement of economic growth and country stability or as measurement of economic growth indicator from monetary sector by Bank of Indonesia. In this research will conducted working capital credit value approval prediction will be provided by commercial bank using support vector machine algorithm that is compared with artificial neutral network algorithm. …”
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Enhancing revenue generation in Bangladesh’s FinTech sector: a comprehensive analysis of real-time predictive customer behavior modeling in AWS using a hybrid OptiBoost-EnsembleX m... by Avijit Chowdhury

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Clustering and Vectorizing Acoustic Emission Events of Large Infrastructures’ Normal Operation by Theocharis Tsenis, Vassilios Kappatos

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Comparison of Rating-based and Inset Lexicon-based Labeling in Sentiment Analysis using SVM (Case Study: GoBiz Application Reviews on Google Play Store) by Hiliah Firda, Pacu Putra, Nabila Rizky Oktadini, Putri Eka Sevtiyuni, Allsela Meiriza

“…It compares two labeling methods—Rating-Based and Inset Lexicon—and evaluates them using the Support Vector Machine (SVM) algorithm. The analysis process includes data selection, text preprocessing, data transformation using TF-IDF, SVM implementation with 10-fold cross-validation, and result visualization through word clouds. …”
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Dynamic Workload Management System in the Public Sector: A Comparative Analysis by Konstantinos C. Giotopoulos, Dimitrios Michalopoulos, Gerasimos Vonitsanos, Dimitris Papadopoulos, Ioanna Giannoukou, Spyros Sioutas

“…Using a dataset encompassing public/private sector experience, educational history, and age, we evaluate the effectiveness of seven machine learning algorithms: Linear Regression, Artificial Neural Networks (ANNs), Adaptive Neuro-Fuzzy Inference System (ANFIS), Support Vector Machine (SVM), Gradient Boosting Machine (GBM), Bagged Decision Trees, and XGBoost in predicting employee capability and optimizing task allocation. …”
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Development of an Optimized Ensemble Least Squares Model for Identifying Potential Deposit Customers by Firman Aziz, Mutia Maulida, Jafar Jafar, Nurafni Shahnyb, Norma Nasir, Ampauleng Ampauleng

“…The proposed Ensemble Least Squares Support Vector Machine (ELS-SVM) algorithm demonstrated superior performance compared to traditional SVM and LS-SVM methods. …”
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Application of machine learning techniques for churn prediction in the telecom business by Raji Krishna, D. Jayanthi, D.S. Shylu Sam, K. Kavitha, Naveen Kumar Maurya, T. Benil

“…These results compare with other ML algorithm such as support vector machines (SVM), gradient boosting (GB), Extreme Gradient Boosting (XGBoost), and light gradient boosting machines (LGBM), The business model provides a practical analysis of customer churn data, enabling accurate forecasts of customers likely to churn. …”
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A big data analysis algorithm for massive sensor medical images by Sarah A. Alzakari, Nuha Alruwais, Shaymaa Sorour, Shouki A. Ebad, Asma Abbas Hassan Elnour, Ahmed Sayed

“…Current anomaly detection methods in healthcare systems, such as artificial intelligence and big data analytics-intracerebral hemorrhage (AIBDA-ICH) and parallel conformer neural network (PCNN), face several challenges, including high resource consumption, inefficient feature selection, and an inability to handle temporal data effectively for real-time monitoring. Techniques like support vector machines (SVM) and the hidden Markov model (HMM) struggle with computational overhead and scalability in large datasets, limiting their performance in critical healthcare applications. …”
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The uneven deployment of algorithms as tools in government: evidence from the use of an expert system by Andrew B. Whitford, Anna M. Whitford

“…This empirical case and this theory of innovation provide broad evidence about the historical utilization of expert systems as algorithms in public sector applications.…”
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Identifying Precipitation Types From Surface Meteorological Variables With Machine Learning by Adrienn VARGA-BALOGH, Ádám LEELŐSSY, Róbert MÉSZÁROS

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Machine Learning Innovations for Improving Mineral Recovery and Processing: A Comprehensive Review* by Korie, Josephmartin Izuchukwu*, Chudi-Ajabor, Ogochukwu Gabriela, Ezeonyema, Chukwudalu Chukwuekezie, Oshim, Francisca Ogechukwu

“…The emergence of ML algorithms, such as Artificial Neural Networks (ANN), Support Vector Machines, and others, trigger this paradigm. …”
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Enhancing tool condition monitoring in friction stir welding with probabilistic neural network algorithm by Balachandar Krishnamurthy, Jegadeeshwaran Rakkiyannan

“…A feature importance study is conducted using a decision tree algorithm, which selects only the most significant features to reduce computational complexity.ResultFeature classification is then performed using various machine learning and deep learning algorithms, including Support Vector Machines (SVM), Multi-Layer Perceptron (MLP), Cascade Correlation, GMDH Polynomial Neural Networks, and Linear Discriminant Analysis Among these classifiers, Probabilistic Neural Networks (PNN) consistently deliver the best results as 91.25% under 1,400 rpm.DiscussionBased on these findings, the Probabilistic Neural Network algorithm is identified as a robust and reliable prediction model for monitoring FSW tool conditions.…”
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Substantiation of Typical Agricultural Areas As a Methodological Basis for the Development of Regional Machine Systems by E. V. Zhalnin, V. A. Zubina

“…It was shown that when developing regional systems of technologies and machines, it is important to take into account all natural agro-climatic conditions and production capabilities in each region’s agricultural sector.Research purpose To develop a methodology for substantiating typical agricultural territories in each agricultural region so that the calculation results obtained for this territory are then generalized for the entire region.Materials and methods The production potential of the region was monitored, the basic assessment criteria were statistically processed and typical agricultural territories were selected according to the minimum deviation of the criteria particular values for the individual regions from the average weighted values for the whole region. …”
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A Comparative Evaluation of Machine Learning Methods for Predicting Student Outcomes in Coding Courses by Zakaria Soufiane Hafdi, Said El Kafhali

“…Our results highlight the long short-term memory (LSTM) algorithm’s robustness achieving the highest accuracy of 94% and an F1-score of 0.87 along with a support vector machine (SVM), indicating high efficacy in predicting student success at the onset of learning coding. …”
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Comprehensive Evaluation of Bankruptcy Prediction in Taiwanese Firms Using Multiple Machine Learning Models by Hung V. Pham, Tuan Chu, Tuan M. Le, Hieu M. Tran, Huong T.K. Tran, Khanh N. Yen, Son V. T. Dao

“…This study developed an advanced bankruptcy prediction model using Support Vector Machines (SVM), Random Forest (RF), and Artificial Neural Network (ANN) algorithms based on datasets from the UCI machine learning repository. …”
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