Spatial Clusters of Gambling Outlet: A Machine Learning Tree-Based Algorithm by Salvador Martínez-Cava, Fernando A. López, MLuz Maté Sánchez-del-Val

“…While public gambling establishments do not exhibit spatial clustering, private gambling establishments show a growth in spatial clustering with dynamic behavior, seeking locations with specific sociodemographic characteristics. A machine learning tree-based algorithm is used to confirm that decisions on where to put new gambling establishments are based on targeting customers with a gambling profile.…”
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A Novel Fuzzy Kernel Extreme Learning Machine Algorithm in Classification Problems by Asli Kaya Karakutuk, Ozer Ozdemir

“…On the JAFFE dataset, the algorithm achieved an average classification accuracy of 94.55% when supported with local binary patterns and 94.27% with a histogram of oriented gradients. …”
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Evaluating Machine Learning Algorithms for Financial Fraud Detection: Insights from Indonesia by Cheng-Wen Lee, Mao-Wen Fu, Chin-Chuan Wang, Muh. Irfandy Azis

“…These findings emphasize the critical need for enhanced fraud detection frameworks, leveraging machine learning algorithms like Random Forest to identify fraud patterns effectively. …”
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Evaluating the Effectiveness of Dimensionality Reduction on Machine Learning Algorithms in Time Series Forecasting by Rida Zaheer, Muhammad Kashif Hanif, Muhammad Umer Sarwar, Ramzan Talib

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Evaluation of machine learning and deep learning algorithms for fire prediction in Southeast Asia by Aditya Eaturu, Krishna Prasad Vadrevu

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Prediction and Optimization of Civil Aviation Flight Delays Based on Machine Learning Algorithms by Qingwei Zhong, Yingxue Yu, Yiru Huang, Tianhang Zhang

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Multivariate machine learning algorithms for energy demand forecasting and load behavior analysis by Farhan Hussain, M. Hasanuzzaman, Nasrudin Abd Rahim

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ADAPTIVE VISION AI by V. Vodyanitskyi, V. Yuskovych-Zhukovska

“…Computer vision technologies rely on pattern recognition, machine learning, and neural networks to allow computers to break down images, interpret data, and identify features. …”
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Enhanced Kidney Stone Detection and Classification Using SVM and LBP Features by Hawkar K. Hama, Hamsa D. Majeed, Goran Saman Nariman

“…The segmentation phase follows, accurately identifying the kidney’s edges and regions of interest for effective feature extraction. The Local Binary Pattern (LBP) technique, combined with the support vector machine (SVM) algorithm serves as the primary components of the proposed model. …”
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Advanced Leaf Classification Using Multi-Layer Perceptron for Smart Crop Management by Sara Mumtaz, Mohammed Alshehri, Yahya AlQahtani, Abdulmonem Alshahrani, Bayan Alabdullah, Haifa F. Alhasson, Hui Liu

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Deciphering algorithmic collusion: Insights from bandit algorithms and implications for antitrust enforcement by Frédéric Marty, Thierry Warin

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Feature Extraction using Histogram of Oriented Gradients and Moments with Random Forest Classification for Batik Pattern Detection by Wafiq Azizah, Soffiana Agustin

“…These findings underscore the efficacy of integrating HOG and Texture Moments with the Random Forest algorithm for automated batik pattern recognition.…”
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Monitoring and Modeling Urban Temperature Patterns in the State of Iowa, USA, Utilizing Mobile Sensors and Geospatial Data by Clemir Abbeg Coproski, Bingqing Liang, James T. Dietrich, John DeGroote

“…Using the random forest machine-learning algorithm and estimated urban morphological variables at varying neighborhood distances derived from 1 m² aerial imagery and derived products from LiDAR data, we created 24 predicted surface temperature models that demonstrated R² coefficients ranging from 0.879 to 0.997 with the majority exceeding an R² of 0.95, all with <i>p</i>-values < 0.001. …”
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Commonalities and differences in gene expression patterns in major depressive disorder and chronic spontaneous urticaria: implications for comorbidity by Yibo Jiang, Wen Li, Lihao Zheng, Nan Ba

“…Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used to characterize putative pathophysiological mechanisms. Subsequently, machine learning algorithms were implemented via 10-fold cross-validation to build transcriptomic classifiers for MDD in a sex-stratified manner. …”
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CRYPTOCURRENCY TIME SERIES FORECASTING MODEL USING GRU ALGORITHM BASED ON MACHINE LEARNING by Melina Melina, Sukono Sukono, Herlina Napitupulu, Norizan Mohamed, Yulison Herry Chrisnanto, Asep ID Hadiana, Valentina Adimurti Kusumaningtyas

“…This research aims to build a cryptocurrency forecasting model with a machine learning-based time series approach using the gated recurrent units (GRU) algorithm. …”
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Machine Learning Algorithms in EEG Analysis of Kleefstra Syndrome: Current Evidence and Future Directions by Katerina D. Tzimourta

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Environmental impacts of economic growth: A STIRPAT analysis using machine learning algorithms by J. Krishnendu, Biswajit Patra

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A Comparative Study Evaluated the Performance of Two-class Classification Algorithms in Machine Learning by Shilan Abdullah Hassan, Maha Sabah Saeed

“…By leveraging Azure Machine Learning's capabilities, researchers and healthcare professionals can analyze large datasets containing patient information and medical records to identify patterns and risk factors associated with heart attacks. …”
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Exploring IRGs as a Biomarker of Pulmonary Hypertension Using Multiple Machine Learning Algorithms by Jiashu Yang, Siyu Chen, Ke Chen, Junyi Wu, Hui Yuan

“…An animal model of PAH was also established to validate hub gene expression patterns. Results: Among the 113 machine learning algorithms, the Lasso + LDA model achieved the highest AUC of 0.741. …”
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Machine heuristic in algorithm aversion: Perceived creativity and effort of output created by or with artificial intelligence by Sigurd Birk Heimstad, Anders Hauge Wien, Tarje Gaustad

“…While previous research has established algorithm aversion across various domains, our findings reveal nuanced patterns in creative contexts. …”
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