Search alternatives:
policy optimization » topology optimization (Expand Search), wolf optimization (Expand Search), process optimization (Expand Search)
which optimization » weight optimization (Expand Search), whale optimization (Expand Search), though optimization (Expand Search)
binary model » final model (Expand Search), injury model (Expand Search), tiny model (Expand Search)
image policy » climate policy (Expand Search), time policy (Expand Search), leave policy (Expand Search)
policy optimization » topology optimization (Expand Search), wolf optimization (Expand Search), process optimization (Expand Search)
which optimization » weight optimization (Expand Search), whale optimization (Expand Search), though optimization (Expand Search)
binary model » final model (Expand Search), injury model (Expand Search), tiny model (Expand Search)
image policy » climate policy (Expand Search), time policy (Expand Search), leave policy (Expand Search)
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ROC curve for binary classification.
Published 2024“…To achieve this, we focused the study on addressing the challenge of image noise, which impacts the performance of deep learning models. …”
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Confusion matrix for binary classification.
Published 2024“…To achieve this, we focused the study on addressing the challenge of image noise, which impacts the performance of deep learning models. …”
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Summary of existing CNN models.
Published 2024“…To achieve this, we focused the study on addressing the challenge of image noise, which impacts the performance of deep learning models. …”
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Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment
Published 2019“…The support vector machine (SVM) classifier is then used to perform parallel training to obtain the optimal SVM classification model, which is then tested. …”
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Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results
Published 2025“…A major challenge in bioprocess simulation is the lack of physical and chemical property databases for biochemicals. A Python-based algorithm was developed for estimating the nonrandom two-liquid (NRTL) model parameters of aqueous binary systems in a straightforward manner from simplified molecular-input line-entry specification (SMILES) strings of substances in a system. …”
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Algorithm for generating hyperparameter.
Published 2024“…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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Results of machine learning algorithm.
Published 2024“…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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Testing results for classifying AD, MCI and NC.
Published 2024“…To achieve this, we focused the study on addressing the challenge of image noise, which impacts the performance of deep learning models. …”
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ROC comparison of machine learning algorithm.
Published 2024“…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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Best optimizer results of Lightbgm.
Published 2024“…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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Best optimizer results of Adaboost.
Published 2024“…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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Best optimizer results of Lightbgm.
Published 2024“…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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Random forest with hyperparameter optimization.
Published 2024“…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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Best optimizer results of KNN.
Published 2024“…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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Best optimizer results of KNN.
Published 2024“…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”