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An integrated machine learning and fractional calculus approach to predicting diabetes risk in women
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Old Drugs, New Indications (Review)
Published 2023-02-01“…Machine learning (ML) algorithms: Bayes classifier, logistic regression, support vector machine, decision tree, random forest and others are successfully used in biochemical pharmaceutical, toxicological research. …”
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Methodology for Estimating the Cost of Construction Equipment Based on the Analysis of Important Characteristics Using Machine Learning Methods
Published 2023-01-01“…The study built and analyzed models using machine learning methods (linear and polynomial regression, decision trees, random forest, support vector machine, and neural network). …”
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Fault Detection in Photovoltaic Systems Using a Machine Learning Approach
Published 2025-01-01“…The proposed fault detection solutions rely on analyzing different algorithms, including Support Vector Machine, Artificial Neural Network, Random Forest, Decision Tree, and Logistic Regression. …”
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Hybrid Model for 6G Network Traffic Prediction and Wireless Resource Optimization
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Sysmon event logs for machine learning-based malware detection
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Mapping Antarctic Blue Ice Areas With Sentinel-2A/B Images and LightGBM Model
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Immune status assessment based on plasma proteomics with meta graph convolutional networks
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Converging efficiency: Computational and fractal insights into parallel non-linear schemes
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Comparative Analysis of Diabetes Prediction Models Using the Pima Indian Diabetes Database
Published 2025-01-01“…The K-means model operates by grouping data points into separate clusters according to their characteristics, achieving an accuracy of 90.04% in diabetes prediction. In comparison, the random forest model, which builds multiple decision trees (DT) to do their predictions, demonstrates superior performance over several widely used algorithms such as K-Nearest Neighbours (KNN), Logistic Regression (LR), DT, Support Vector Machines (SVM), and Gradient Boosting (GB). …”
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Multi-scenario Dynamic Simulation and Optimization of Urban Ventilation Environment: A Case Study of Taiyuan Metropolitan Area
Published 2025-05-01“…Then, a prediction model is constructed based on the random forest algorithm. The land use types and ventilation environment of multiple scenarios in 2010 and 2020 are input into the validated prediction model to simulate changes in the future ventilation environment. …”
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Shape Penalized Decision Forests for Imbalanced Data Classification
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Downscaling of Soil Moisture Map using Sentinel Radar Satellite Images and Distribution Analysis in the West of Iran
Published 2020-12-01“…The results of this study also confirm that the algorithm used in this research can effectively lead to the extraction of the soil surface moisture layer with a higher resolution…”
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Eco-Driving Level Evaluation Model for Electric Buses Entering and Leaving Stops
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