Search alternatives:
codon optimization » wolf optimization (Expand Search)
all classification » a classification (Expand Search), ad classification (Expand Search), atc classification (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data all » data a (Expand Search)
codon optimization » wolf optimization (Expand Search)
all classification » a classification (Expand Search), ad classification (Expand Search), atc classification (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data all » data a (Expand Search)
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Implementation of Adaptive Genetic Algorithm for classification problems
Published 2022“…<p>Genetic algorithms are one of the most</p> <p>commonly used approaches in data mining. …”
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Data Sheet 1_Bundled assessment to replace on-road test on driving function in stroke patients: a binary classification model via random forest.docx
Published 2025“…The subject was classified as either Success or Unsuccess group according to whether they had completed the on-road test. A random forest algorithm was then applied to construct a binary classification model based on the data obtained from the two groups.…”
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Random forest algorithm: Method and example results.
Published 2019“…(<b>D</b>) Schematic illustration of arrays input into Random Forest algorithm. Columns correspond to gene, rows to pixels in the top projection data set. …”
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Association between crowding and oral habits.
Published 2025“…The dataset was created, and AI-based binary classification models for malocclusion were developed using an automated machine learning platform (DataRobot) to construct three algorithms for determining malocclusion (deep bite, maxillary protrusion, and crowding). …”
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Association between deep bite and oral habits.
Published 2025“…The dataset was created, and AI-based binary classification models for malocclusion were developed using an automated machine learning platform (DataRobot) to construct three algorithms for determining malocclusion (deep bite, maxillary protrusion, and crowding). …”
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Breakdown of participants by residential area.
Published 2025“…The dataset was created, and AI-based binary classification models for malocclusion were developed using an automated machine learning platform (DataRobot) to construct three algorithms for determining malocclusion (deep bite, maxillary protrusion, and crowding). …”
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Each variable for the dataset.
Published 2025“…The dataset was created, and AI-based binary classification models for malocclusion were developed using an automated machine learning platform (DataRobot) to construct three algorithms for determining malocclusion (deep bite, maxillary protrusion, and crowding). …”
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Telehealth.
Published 2025“…The paper utilized the binary Logistic Regression and the random forest algorithm to predict the participants’ attitudes towards the ease of using Telehealth services. …”
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Kernel Density Plot of Effort Expectancy Scores.
Published 2025“…The paper utilized the binary Logistic Regression and the random forest algorithm to predict the participants’ attitudes towards the ease of using Telehealth services. …”
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Natural language processing and machine learning algorithm to identify brain MRI reports with acute ischemic stroke
Published 2019“…Labeling for AIS was performed manually, identifying clinical notes. We applied binary logistic regression, naïve Bayesian classification, single decision tree, and support vector machine for the binary classifiers, and we assessed performance of the algorithms by F1-measure. …”
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