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Comparative Analysis of Supervised Classification Algorithms for Residential Water End Uses
Published 2024-06-01Get full text
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Machine Learning Classifiers Based Classification For IRIS Recognition
Published 2021-05-01Get full text
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Distress-Based Pavement Condition Assessment Using Artificial Intelligence: A Case Study of Egyptian Roads
Published 2025-05-01Get full text
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Predicting climate-driven shift of the East Mediterranean endemic Cynara cornigera Lindl
Published 2025-02-01Get full text
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Casualty Analysis of the Drivers in Traffic Accidents in Turkey: A CHAID Decision Tree Model
Published 2024-12-01“…The difference between the success of the models with regard to accuracy obtained through dominant and investigated factors is only 5.0%. Random Forests, Naïve Bayes, and CHAID (Chi-squared Automatic Interaction Detection) models were established and compared as decision tree algorithms. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022-12-01“…Subsequently, DDoS attack detection is performed based on random forest (RF) and decision tree (DT) algorithms. …”
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Tree inventory analysis using AI and GIS in Uzbekistan: A case study from Tashkent
Published 2025-01-01Get full text
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Exploring machine learning classification for community based health insurance enrollment in Ethiopia
Published 2025-07-01Get full text
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Microseismic Data-Driven Short-Term Rockburst Evaluation in Underground Engineering with Strategic Data Augmentation and Extremely Randomized Forest
Published 2024-11-01“…The insights derived from this research provide a reference for microseismic data-based short-term rockburst prediction when faced with class imbalance and multicollinearity.…”
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Machine Learning-Based Approach for HIV/AIDS Prediction: Feature Selection and Data Balancing Strategy
Published 2025-03-01“…Nine machine learning algorithms, including Decision Tree, Random Forest, XGBoost, LightGBM, Gradient Boosting, Support Vector Machine, AdaBoost, and Logistic Regression, are tested for classification. …”
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Surface water quality assessment for drinking and pollution source characterization: A water quality index, GIS approach, and performance evaluation utilizing machine learning anal...
Published 2025-07-01“…This study sought to evaluate the region's surface water quality and sources of contamination using machine learning (ML) methods such as Logistic Regression (LOR), Random Forest (RF), Artificial Neural Network (ANN), Support Vector Machine (SVM), Decision Tree (DT), and K-Nearest Neighbor (KNN). …”
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