بدائل البحث:
function optimization » reaction optimization (توسيع البحث), formulation optimization (توسيع البحث), generation optimization (توسيع البحث)
web optimization » b optimization (توسيع البحث), yet optimization (توسيع البحث), led optimization (توسيع البحث)
basis function » loss function (توسيع البحث), brain function (توسيع البحث), barrier function (توسيع البحث)
binary basis » binary mask (توسيع البحث), binary pairs (توسيع البحث)
lines based » lens based (توسيع البحث), genes based (توسيع البحث), lines used (توسيع البحث)
function optimization » reaction optimization (توسيع البحث), formulation optimization (توسيع البحث), generation optimization (توسيع البحث)
web optimization » b optimization (توسيع البحث), yet optimization (توسيع البحث), led optimization (توسيع البحث)
basis function » loss function (توسيع البحث), brain function (توسيع البحث), barrier function (توسيع البحث)
binary basis » binary mask (توسيع البحث), binary pairs (توسيع البحث)
lines based » lens based (توسيع البحث), genes based (توسيع البحث), lines used (توسيع البحث)
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Cell fishing: A similarity based approach and machine learning strategy for multiple cell lines-compound sensitivity prediction
منشور في 2019"…<div><p>The prediction of cell-lines sensitivity to a given set of compounds is a very important factor in the optimization of in-vitro assays. …"
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Classification performance after optimization.
منشور في 2025"…We applied this hybrid strategy to a Radial Basis Function Network (RBFN), and validated its performance improvements through extensive experiments, including ANOVA and Wilcoxon tests for both feature selection and optimization phases. …"
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ANOVA test for optimization results.
منشور في 2025"…We applied this hybrid strategy to a Radial Basis Function Network (RBFN), and validated its performance improvements through extensive experiments, including ANOVA and Wilcoxon tests for both feature selection and optimization phases. …"
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Wilcoxon test results for optimization.
منشور في 2025"…We applied this hybrid strategy to a Radial Basis Function Network (RBFN), and validated its performance improvements through extensive experiments, including ANOVA and Wilcoxon tests for both feature selection and optimization phases. …"
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Wilcoxon test results for feature selection.
منشور في 2025"…We applied this hybrid strategy to a Radial Basis Function Network (RBFN), and validated its performance improvements through extensive experiments, including ANOVA and Wilcoxon tests for both feature selection and optimization phases. …"
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Feature selection metrics and their definitions.
منشور في 2025"…We applied this hybrid strategy to a Radial Basis Function Network (RBFN), and validated its performance improvements through extensive experiments, including ANOVA and Wilcoxon tests for both feature selection and optimization phases. …"
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Statistical summary of all models.
منشور في 2025"…We applied this hybrid strategy to a Radial Basis Function Network (RBFN), and validated its performance improvements through extensive experiments, including ANOVA and Wilcoxon tests for both feature selection and optimization phases. …"
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Feature selection results.
منشور في 2025"…We applied this hybrid strategy to a Radial Basis Function Network (RBFN), and validated its performance improvements through extensive experiments, including ANOVA and Wilcoxon tests for both feature selection and optimization phases. …"
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ANOVA test for feature selection.
منشور في 2025"…We applied this hybrid strategy to a Radial Basis Function Network (RBFN), and validated its performance improvements through extensive experiments, including ANOVA and Wilcoxon tests for both feature selection and optimization phases. …"
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Classification performance of ML and DL models.
منشور في 2025"…We applied this hybrid strategy to a Radial Basis Function Network (RBFN), and validated its performance improvements through extensive experiments, including ANOVA and Wilcoxon tests for both feature selection and optimization phases. …"
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Severe pediatric brucellosis prediction model in Yunnan Province, China, 2015–2024.
منشور في 2025"…<b>(b)</b> Variable selection using the BORUTA algorithm to identify key variables associated with the prediction of severe disease, with the selected variables marked by the red dashed lines. …"
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Table_1_bSRWPSO-FKNN: A boosted PSO with fuzzy K-nearest neighbor classifier for predicting atopic dermatitis disease.docx
منشور في 2023"…</p>Methods<p>This paper establishes a medical prediction model for the first time on the basis of the enhanced particle swarm optimization (SRWPSO) algorithm and the fuzzy K-nearest neighbor (FKNN), called bSRWPSO-FKNN, which is practiced on a dataset related to patients with AD. …"
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Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat.
منشور في 2025"…Multiple SVM models were trained and evaluated, including configurations with linear and RBF (Radial Basis Function) kernels. </p><p dir="ltr">Additionally, an exhaustive hyperparameter search was performed using GridSearchCV to optimize the C, gamma, and kernel parameters (testing 'linear,' 'rbf,' 'poly,' and 'sigmoid'), aiming to find the highest-performing configuration. …"
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Supplementary Material 8
منشور في 2025"…</li><li><b>XGboost: </b>An optimized gradient boosting algorithm that efficiently handles large genomic datasets, commonly used for high-accuracy predictions in <i>E. coli</i> classification.…"
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Table_1_Distinguishing HapMap Accessions Through Recursive Set Partitioning in Hierarchical Decision Trees.pdf
منشور في 2021"…Subsequently, we build a hierarchical decision tree in which a specific path represents the selected markers and the homogenous genotypes that can be used to distinguish one accession from others in the HapMap population. Based on these algorithms, we developed a web tool named MAD-HiDTree (Multiple Accession Distinguishment-Hierarchical Decision Tree), designed to analyze a user-input genotype matrix and construct a hierarchical decision tree. …"