An Improved Genghis Khan Optimizer based on Enhanced Solution Quality Strategy for Global Optimization and Feature Selection Problems by Abdel-Salam, Mahmoud

“…Feature selection (FS) is the activity of defining the most contributing feature subset among all used features to improve the superiority of datasets with a large number of dimensions by selecting significant features and eliminating redundant and irrelevant ones. …”
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Application of Data Mining to Predict and Diagnose Diabetic Retinopathy by Haniyeh, Maryam

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Assessment and Performance Analysis of Machine Learning Techniques for Gas Sensing E-nose Systems by Mahmood, Lubna Syeda

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A Novel Non-Invasive Estimation of Respiration Rate From Motion Corrupted Photoplethysmograph Signal Using Machine Learning Model by Md. Nazmul Islam Shuzan (16888827)

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Optimizing Document Classification: Unleashing the Power of Genetic Algorithms by 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. …”

Video features with impact on user quality of experience by Abbas, Nadine

“…After collecting the QoE assessments, the supervised training data set is developed and imported into Rapid-Miner data mining tool. The feature evaluation is performed first using forward elimination feature selection algorithm, and second using decision tree classification to extract and sort the features that highly affect the subjective QoE. …”
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Comparative Study on Arabic Text Classification: Challenges and Opportunities by Abualigah, Laith

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Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms by Arafat Rahman (8065562)

“…A machine learning classification pipeline is developed using multi-domain feature extraction (time, frequency, time-frequency), feature selection (Gini impurity), classifier design, and score level fusion. …”

A Novel Fault Diagnosis of Uncertain Systems Based on Interval Gaussian Process Regression: Application to Wind Energy Conversion Systems by Majdi Mansouri (16869885)

“…In the proposed IGPR-RF technique, the effective interval-valued nonlinear statistical features are extracted and selected using the IGPR model and then fed to the RF algorithm for fault classification purposes. …”

Regression test selection for trusted database applications by Haraty, Ramzi A.

“…Our proposed algorithms automate an important portion of the regression testing process, and they operate more efficiently than most other regression test selection algorithms. …”
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Multi Self-Organizing Map (SOM) Pipeline Architecture for Multi-View Clustering by Saadia Jamil (22045946)

“…This raises basic problems like the need for a dimensionality reduction technique for optimal selection of features, fusing the data of different views, and maintaining the inter- and intra-consensus of the multiview dataset. …”

The effects of data balancing approaches: A case study by Paul Mooijman (4453189)

A Hybrid Fault Detection and Diagnosis of Grid-Tied PV Systems: Enhanced Random Forest Classifier Using Data Reduction and Interval-Valued Representation by Khaled Dhibi (16891524)

“…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. …”

Toward automatic motivator selection for autism behavior intervention therapy by Siyam, Nur

“…To evaluate the motivator selection feature, we conduct a study involving a group of teachers and therapists and assess how the added feature aids the participants in their decision-making process of selecting a motivator. …”
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The automation of the development of classification models and improvement of model quality using feature engineering techniques by Sjoerd Boeschoten (17347045)

“…In this article, we propose a framework that combines feature engineering techniques such as data imputation, transformation, and class balancing to compare the performance of different prediction models and select the best final model based on predefined parameters. …”

Particle swarm optimization algorithm: review and applications by Abualigah, Laith

“…This paper surveys the published papers in PSO algorithms. Twenty research papers are analyzed and classified according to the implementation area used by the PSO algorithm (neural networks, feature selection, and data clustering). …”
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StackDPPred: Multiclass prediction of defensin peptides using stacked ensemble learning with optimized features by Muhammad Arif (769250)

“…Additionally, we applied the local interpretable model-agnostic explanations (LIME) algorithm to understand the contribution of selected features to the overall prediction. …”

Strategies for Reliable Stress Recognition: A Machine Learning Approach Using Heart Rate Variability Features by Mariam Bahameish (19255789)

“…To account for limitations associated with small datasets, robust strategies were implemented based on methodological recommendations for ML with a limited dataset, including data segmentation, feature selection, and model evaluation. Our findings highlight that the random forest model achieved the best performance in distinguishing stress from non-stress states. …”

Enhanced PSO-Based NN for Failures Detection in Uncertain Wind Energy Systems by Khaled Dhibi (16891524)

“…Therefore, an enhanced particle swarm optimization (PSO), data reduction, and interval-valued representation are proposed. First, a feature selection tool using PSO Algorithm is developed. …”

Fast Text Classification using Lean Gradient Descent Feed Forward Neural Network for Category Feature Augmentation by Attieh, Joseph

“…Performing text classification requires features that effectively represent the content and the meaning of textual documents. …”
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