A Novel Big Data Classification Technique for Healthcare Application Using Support Vector Machine, Random Forest and J48 حسب Al-Manaseer, Hitham

"…This was done by studying the performance of three well-known classification algorithms Random Forest Classifier (RFC), Support Vector Machine (SVM), and Decision Tree-J48 (J48), to predict the probability of heart attack. …"
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A systematic review of recent advances in the application of machine learning in membrane-based gas separation technologies حسب Farideh Abdollahi (22303153)

"…The fingerprinting and descriptors are two commonly approach for polymer featurization. In terms of algorithms, <u>neural networks</u> (NNs), random forest (RF), and gaussian process regression (GPR) are among the most extensively applied methods. …"

Anomaly Detection Based Framework for Profile Monitoring حسب Al-Rahim, Nour Al-Huda Z. Al-Abed

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Optimizing Document Classification: Unleashing the Power of Genetic Algorithms حسب Ghulam Mustafa (458105)

"…Additionally, our proposed model optimizes the features using a genetic algorithm. Optimal feature selection performances a crucial role in this domain, enhancing the overall accuracy of the document classification system while reducing the time complexity associated with selecting the most relevant features from this large-dimensional space. …"

Mining airline data for CRM strategies. (c2006) حسب Maalouf, Lena

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Indexing Arabic texts using association rule data mining حسب Haraty, Ramzi A.

"…The model denotes extracting new relevant words by relating those chosen by previous classical methods to new words using data mining rules. …"
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Scalable Nonparametric Supervised Learning for Streaming and Massive Data: Applications in Healthcare Monitoring and Credit Risk حسب Mohamed Chaouch (17983846)

"…Additionally, an online classifier is developed for streaming data, combining online PCA with a kernel-based recursive classifier using a stochastic approximation algorithm. …"

Artificial intelligence-based methods for fusion of electronic health records and imaging data حسب Farida Mohsen (16994682)

"…In our analysis, a typical workflow was observed: feeding raw data, fusing different data modalities by applying conventional machine learning (ML) or deep learning (DL) algorithms, and finally, evaluating the multimodal fusion through clinical outcome predictions. …"

A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai حسب ALGHANEM, HANI SUBHI MOHD

"…My research aims to develop a data-driven decision support framework for fleet management, focusing on leveraging advanced algorithms, including decision trees and random forests, to generate domain-specific AI models. …"
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Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms حسب Arafat Rahman (8065562)

"…We also developed a binary template matching-based algorithm, which gives 93.64% accuracy 6X faster. …"

حوكمة الذكاء الاصطناعي ضمن أحكام القانون الدولي لحقوق الإنسان حسب Hilal, Ghofran M. I.

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Predict Student Success and Performance factors by analyzing educational data using data mining techniques حسب ATIF, MUHAMMAD

"…The research study is performed as experimental analysis and develop models from nine machine learning algorithms including KNN, Naïve Bayes, SVM, Logistic regression, Decision Tree, Random forest, Adaboost, Bagging Classifier, and voting Classifier. …"
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Future Prediction of COVID-19 Vaccine Trends Using a Voting Classifier حسب Syed Ali Jafar Zaidi (19563178)

"…Modern ML models are used for prediction, prioritization, and decision making. Multiple ML algorithms are used to improve decision-making at different aspects after forecasting. …"

Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks حسب Najam Us Sahar Riyaz (22927843)

"…This work identifies the most reliable machine learning (ML) strategies for forecasting corrosion inhibitor efficiency before synthesis, thereby shortening development cycles and reducing experimental cost. Drawing on more than fifteen harmonized datasets that span pyrimidines, ionic liquids, graphene oxides, and additional compound families, we benchmark traditional algorithms, such as artificial neural networks, support vector machines, k-nearest neighbors, random forests, against advanced graph-based and deep architectures including three-level directed message-passing neural networks, 2D3DMol-CIC, and graph convolutional networks. …"

Prediction of pressure gradient for oil-water flow: A comprehensive analysis on the performance of machine learning algorithms حسب Md Ferdous Wahid (13485799)

"…<p dir="ltr">Pressure gradient (PG) in liquid-liquid flow is one of the key components to design an energy-efficient transportation system for wellbores. This study aims to develop five robust machine learning (ML) algorithms and their fusions for a wide range of flow patterns (FP) regimes. …"

A collaborative filtering recommendation framework utilizing social networks حسب Aamir Fareed (17019087)

Gene selection for microarray data classification based on Gray Wolf Optimizer enhanced with TRIZ-inspired operators حسب Abu Zitar, Raed

"…The outcomes of the DNA microarray is a table/matrix, called gene expression data. Pattern recognition algorithms are widely applied to gene expression data to differentiate between health and cancerous patient samples. …"
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Random Forest Bagging and X‐Means Clustered Antipattern Detection from SQL Query Log for Accessing Secure Mobile Data حسب Rajesh Kumar Dhanaraj (19646269)

"…<p dir="ltr">In the current ongoing crisis, people mostly rely on mobile phones for all the activities, but query analysis and mobile data security are major issues. Several research works have been made on efficient detection of antipatterns for minimizing the complexity of query analysis. …"

Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval حسب Mohammed Tahar Habib Kaib (21633176)

"…In this paper, the proposed algorithm selects relevant observations from the original data set by utilizing a class interval technique (i.e. histogram) to maintain a bunch of representative samples from each bin. …"

Reinforced steering Evolutionary Markov Chain for high-dimensional feature selection حسب Atiq ur Rehman (3044409)

"…<p>The increasing accessibility of extensive datasets has amplified the importance of extracting insights from high-dimensional data. However, the task of selecting relevant features in these high-dimensional spaces is made more difficult due to the curse of dimensionality. …"