Search alternatives:
elimination algorithm » maximization algorithm (Expand Search), optimization algorithms (Expand Search), segmentation algorithm (Expand Search)
driven optimization » design optimization (Expand Search), guided optimization (Expand Search), dose optimization (Expand Search)
data feature » data figure (Expand Search), each feature (Expand Search), a feature (Expand Search)
image driven » climate driven (Expand Search), wave driven (Expand Search), mapk driven (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
elimination algorithm » maximization algorithm (Expand Search), optimization algorithms (Expand Search), segmentation algorithm (Expand Search)
driven optimization » design optimization (Expand Search), guided optimization (Expand Search), dose optimization (Expand Search)
data feature » data figure (Expand Search), each feature (Expand Search), a feature (Expand Search)
image driven » climate driven (Expand Search), wave driven (Expand Search), mapk driven (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
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Integrative Clinical and Bio-mechanical Features Predict In-Hospital Trauma Mortality
Published 2024Subjects: -
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Variable Selection and Estimation for Misclassified Binary Responses and Multivariate Error-Prone Predictors
Published 2023“…The simultaneous appearance of these complex features make data analysis become challenging. To address those concerns, we propose a valid inferential method to deal with measurement error and handle variable selection simultaneously. …”
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Design and implementation of the Multiple Criteria Decision Making (MCDM) algorithm for predicting the severity of COVID-19.
Published 2021“…<p>(A). The MCDM algorithm-Stage 1. Preprocessing, this stage is the process of refining the collected raw data to eliminate noise, including correlation analysis and feature selection based on P values. …”
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Data_Sheet_3_sigFeature: Novel Significant Feature Selection Method for Classification of Gene Expression Data Using Support Vector Machine and t Statistic.docx
Published 2020“…Many feature selection algorithms have been developed including the support vector machine recursive feature elimination procedure (SVM-RFE) and its variants. …”
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Data_Sheet_2_sigFeature: Novel Significant Feature Selection Method for Classification of Gene Expression Data Using Support Vector Machine and t Statistic.docx
Published 2020“…Many feature selection algorithms have been developed including the support vector machine recursive feature elimination procedure (SVM-RFE) and its variants. …”
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Data_Sheet_1_sigFeature: Novel Significant Feature Selection Method for Classification of Gene Expression Data Using Support Vector Machine and t Statistic.docx
Published 2020“…Many feature selection algorithms have been developed including the support vector machine recursive feature elimination procedure (SVM-RFE) and its variants. …”
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Thesis-RAMIS-Figs_Slides
Published 2024“…<br><br>Finally, although the developed concepts, ideas and algorithms have been developed for inverse problems in geostatistics, the results are applicable to a wide range of disciplines where similar sampling problems need to be faced, included but not limited to design of communication networks, optimal integration and communication of swarms of robots and drones, remote sensing.…”
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