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A comparative analysis of machine learning algorithms for diabetes prediction
Published 2024“…The methodology involves data collection, pre-processing, and training the algorithms using k-fold cross-validation. …”
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Classification for large number of variables with two imbalanced groups
Published 2020“…This study proposed two algorithms of classification namely Algorithm 1 and Algorithm 2 which combine resampling, variable extraction, and classification procedure. …”
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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud
Published 2023“…The best algorithm will not be the same for all the data sets. …”
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Prediction of payment method in convenience stores using machine learning
Published 2023“…This study explores the application of machine learning techniques, specifically the Random Forest algorithm, to predict payment modes in the context of the Indonesian community. …”
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Malware Classification and Detection using Variations of Machine Learning Algorithm Models
Published 2025“…Types of attacks can be Ping of Death, flooding, remote-controlled attacks, UDP flooding, and Smurf Attacks. Attack data was obtained from the ClaMP dataset, which has an unbalanced data set, and has very high noise, so it is necessary to analyze data packets in network logs and optimize feature extraction which is then analyzed statistically with machine learning algorithms. …”
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Forecasting and Trading of the Stable Cryptocurrencies With Machine Learning and Deep Learning Algorithms for Market Conditions
Published 2023“…Thus, this proposed system employs a data science-based framework and six highly advanced data-driven Machine learning and Deep learning algorithms: Support Vector Regressor, Auto-Regressive Integrated Moving Average (ARIMA), Facebook Prophet, Unidirectional LSTM, Bidirectional LSTM, Stacked LSTM. …”
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Optimal timber transportation planning in tropical hill forest using bees algorithm
Published 2022“…The model uses grid cell-sized 10 m x 10 m characterised with timber locations, volume and fixed and variable costs to represent the study area. …”
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…The classification algorithm used in this research is the Convolutional Neural Network (CNN) algorithm. …”
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Optimized clustering with modified K-means algorithm
Published 2021“…Clustering technique is able to find hidden patterns and to extract useful information from huge data. Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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Enhancing project completion date prediction using a hybrid model: rule-based algorithm and machine learning algorithm
Published 2025“…The study employs a hybrid predictive model that combines Big Data technologies, Extract Load Transfer (ELT) processes, rule-based algorithms (RBA), machine learning (ML), and Power BI visualizations. …”
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Coronary artery stenosis detection and visualization / Tang Sze Ling
Published 2015“…The performance evaluation results show that the stenosis detection algorithm performs better average sensitivity than several state-of-the-art algorithms.…”
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Multi road marking detection system for autonomous car using hybrid- based method
Published 2018“…With an accuracy of 96.53% using LVRI and 99.33% using the T. Wu datasets, the proposed algorithm able to detect almost all types of road markings. …”
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Analyzing The Potential Of Genetic Algorithm For Maximum Power Point Tracking In Wind Energy Conversion System In Malaysia
Published 2023“…A genetic algorithm is used to further optimised the control strategy by finding the optimised variable for the controller. …”
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Development of an effective clustering algorithm for older fallers
Published 2022“…Using feature extraction with the t-SNE and the K-means clustering algorithm, subjects were clustered into low, intermediate A, intermediate B and high fall risk groups which corresponded with fall occurrence of 13%, 19%, 21% and 31% respectively. …”
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A review of the inter-correlation of climate change, air pollution and urban sustainability using novel machine learning algorithms and spatial information science
Published 2021“…The study also revealed that machine learning algorithms such as random forest, gradient boosting machine, and classification and regression trees (CART) accurately predict air pollution hazard when integrated with spatial models. …”
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Shunt active power filter using hybrid fuzzy-proportional and crisp-integral control algorithms for total harmonic distortion improvement
Published 2016“…First, unified ADALINEs based fundamental component extraction algorithm is proposed for dual functionality. …”
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