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Variable Selection in Data Analysis: A Synthetic Data Toolkit
Published 2024Subjects: Get full text
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TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection
Published 2020“…TIDCS reduces the number of features in the input data based on a new algorithm for feature selection. …”
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Application of Data Mining to Predict and Diagnose Diabetic Retinopathy
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Genetic-Algorithm-Based Neural Network for Fault Detection and Diagnosis: Application to Grid-Connected Photovoltaic Systems
Published 2022“…This is addressed such that the genetic algorithm (GA) technique is used for selecting the best features and the artificial neural network (ANN) classifier is applied for fault diagnosis. …”
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Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms
Published 2022“…The outcomes revealed that these ML algorithms can be useful in predicting ground losses during wild blueberry harvesting in the selected fields.…”
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UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data
Published 2024Subjects: -
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Limiting the Collection of Ground Truth Data for Land Use and Land Cover Maps with Machine Learning Algorithms
Published 2022“…The accuracy of these algorithms was assessed with standard statistical measures and ground truth data randomly collected in Prince Edward Island, Canada. …”
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NOVEL STACKING CLASSIFICATION AND PREDICTION ALGORITHM BASED AMBIENT ASSISTED LIVING FOR ELDERLY
Published 2022“…This study's dataset was sourced from the Kaggle machine learning repository, and it refers to data gathering from wearable IoT devices. The experimental outcomes demonstrate the proposed MCFS, NCA, and NSCP algorithms work more effectively than previous feature selection, clustering and classification algorithms, respectively, in terms of accuracy, sensitivity, specificity, precision, recall, f-measure and execution time. …”
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Application of Machine Learning Algorithms to Enhance Money Laundering and Financial Crime Detection
Published 2011“…In order to analyze the performance of machine learning algorithms, data was provided by a bank to be used for educational purposes and shall remain undisclosed. …”
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An enhanced quorum selection algorithm
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An Improved Quorum Selection Algorithm
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Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks
Published 2025“…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R<sup>2</sup> = 0.05 to 0.99 in a representative thiophene set. …”
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A Hybrid Fault Detection and Diagnosis of Grid-Tied PV Systems: Enhanced Random Forest Classifier Using Data Reduction and Interval-Valued Representation
Published 2021“…In the proposed FDD approach, named interval reduced kernel PCA (IRKPCA)-based Random Forest (IRKPCA-RF), the feature extraction and selection phase is performed using the IRKPCA models while the fault classification is ensured using the RF algorithm. …”
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Interval-Valued SVM Based ABO for Fault Detection and Diagnosis of Wind Energy Conversion Systems
Published 2022“…Next, as a feature selection tool, an improved extension of Artificial Butterfly Optimization (ABO) algorithm is used in order to extract the significant features from data and improve the diagnosis results of multiscale interval SVM. …”
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UAV Trajectory Planning for Data Collection from Time-Constrained IoT Devices
Published 2019“…This motivates the utilization of unmanned aerial vehicles (UAVs) to offload traffic from existing wireless networks by collecting data from time-constrained IoT devices with performance guarantees. …”
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Unsupervised outlier detection in multidimensional data
Published 2022“…<p>Detection and removal of outliers in a dataset is a fundamental preprocessing task without which the analysis of the data can be misleading. …”