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Effect of Hyperparameter Tuning on Performance on Classification model
Published 2025-06-01“…This research aims to analyze the effect of hyperparameter tuning on the performance of Logistic Regression, K-Nearest Neighbours, Support Vector Machine, Decision Tree, Random Forest, Random Forest Classifier, Naive Bayes algorithms. …”
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The Effect of Hyperparameters on Faster R-CNN in Face Recognition Systems
Published 2025-05-01“…This study aims to develop a face recognition system using a Faster R-CNN architecture, optimized through hyperparameter tuning. This research utilizes the "Face Recognition Dataset" from Kaggle, which comprises 2,564 face images across 31 classes. …”
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A review on multi-fidelity hyperparameter optimization in machine learning
Published 2025-04-01“…Tuning hyperparameters effectively is crucial for improving the performance of machine learning models. …”
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Hyperparameter optimization of machine learning models for predicting actual evapotranspiration
Published 2025-06-01“…This findings encourage future research using varied input combinations and advanced modeling approaches for AET accurate prediction.…”
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A Comparison of AutoML Hyperparameter Optimization Tools For Tabular Data
Published 2023-05-01Get full text
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Investigation into the Hyperparameters of Error-Based Adaptive Sampling Approach for Surrogate Modeling
Published 2024-12-01Get full text
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Modified particle swarm optimization (MPSO) optimized CNN’s hyperparameters for classification
Published 2025-02-01“…This research demonstrates the performance of the MPSO algorithm in optimizing CNN architectures, highlighting its potential for improving image recognition tasks.…”
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Optimizing Depression Classification Using Combined Datasets and Hyperparameter Tuning with Optuna
Published 2025-03-01“…This research focuses on the depression states classification of EEG signals using the EEGNet model optimized with Optuna. …”
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Optimizing SVM Performance through Combinatorial Hyperparameter Tuning and Model Selection
Published 2025-06-01“…Future research can focus on enhancing SVM performance for large-scale datasets and exploring ensemble techniques or deep learning models to enhance its applications in real-world scenarios.…”
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Enhancing CNN-based network intrusion detection through hyperparameter optimization
Published 2025-06-01“…Abstracts: This research investigates the optimization of hyperparameters in Convolutional Neural Networks (CNNs) to enhance the performance of Network Intrusion Detection Systems (NIDS). …”
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Investigating the hyperparameter space of deep neural network models for reaction coordinates
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A Survey on Hyperparameters Optimization of Deep Learning for Time Series Classification
Published 2024-01-01“…The adoption of deep learning has advanced TSC, however its performance is sensitive to hyperparameters configuration. Manual tuning of high-dimensional hyperparameters can be labor intensive, leading to a preference for automatic hyperparameters optimization (HPO) methods. …”
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Hyperparameter optimization of apple leaf dataset for the disease recognition based on the YOLOv8
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Heuristic based federated learning with adaptive hyperparameter tuning for households energy prediction
Published 2025-04-01Get full text
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OPTIMIZED FACEBOOK PROPHET FOR MPOX FORECASTING: ENHANCING PREDICTIVE ACCURACY WITH HYPERPARAMETER TUNING
Published 2025-03-01“…The results show that hyperparameter tuning significantly enhances forecasting accuracy. …”
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Optimizing forensic file classification: enhancing SFCS with βk hyperparameter tuning
Published 2025-03-01“…Incorporating βk into SFCS allowed the proposed model to remove 278 k irrelevant files from the corpus and identify 5.6 k suspicious files by extracting 700 blacklisted keywords. Furthermore, this research implemented hyperparameter optimization and hyperplane maximization, resulting in a file classification accuracy of 94.6%, 94.4% precision and 96.8% recall within O(n log n) complexity.…”
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Ensemble genetic and CNN model-based image classification by enhancing hyperparameter tuning
Published 2025-01-01“…The objective of this research is to improve the CNN-based image classification system by utilizing the advantages of ensemble learning and GA. …”
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