Showing 1 - 20 results of 901 for search 'hyperparameter research', query time: 0.10s Refine Results
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    Effect of Hyperparameter Tuning on Performance on Classification model by Muhammad Sholeh, Uning Lestari, Dina Andayati

    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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    Article
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    The Effect of Hyperparameters on Faster R-CNN in Face Recognition Systems by Jasman Pardede, Khairul Rijal

    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 by Jonghyeon Won, Hyun-Suk Lee, Jang-Won Lee

    Published 2025-04-01
    “…Tuning hyperparameters effectively is crucial for improving the performance of machine learning models. …”
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    Article
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    Hyperparameter optimization of machine learning models for predicting actual evapotranspiration by Chalachew Muluken Liyew, Elvira Di Nardo, Stefano Ferraris, Rosa Meo

    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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    Modified particle swarm optimization (MPSO) optimized CNN’s hyperparameters for classification by Murinto Murinto, Sri Winiarti

    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 by Ștefana Duță, Alina Elena Sultana

    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 by Hassan Tariq, Mehwish Majeed, Mueed Ahmad

    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 by Antanios Kaissar, Ali Bou Nassif, Bassel Soudan, MohammadNoor Injadat

    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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    A Survey on Hyperparameters Optimization of Deep Learning for Time Series Classification by Ayuningtyas Hari Fristiana, Syukron Abu Ishaq Alfarozi, Adhistya Erna Permanasari, Mahardhika Pratama, Sunu Wibirama

    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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    OPTIMIZED FACEBOOK PROPHET FOR MPOX FORECASTING: ENHANCING PREDICTIVE ACCURACY WITH HYPERPARAMETER TUNING by Nur Alamsyah, Venia Restreva Danestiara, Budiman Budiman, Reni Nursyanti, Elia Setiana, Acep Hendra

    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 by D. Paul Joseph, Viswanathan Perumal

    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 by Wajahat Hussain, Muhammad Faheem Mushtaq, Mobeen Shahroz, Urooj Akram, Ehab Seif Ghith, Mehdi Tlija, Tai-hoon Kim, Imran Ashraf

    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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