Search alternatives:
weights optimization » weight optimization (Expand Search), weights initialization (Expand Search), design optimization (Expand Search)
lead optimization » global optimization (Expand Search), swarm optimization (Expand Search), whale optimization (Expand Search)
class lead » class lca (Expand Search), class left (Expand Search)
weights optimization » weight optimization (Expand Search), weights initialization (Expand Search), design optimization (Expand Search)
lead optimization » global optimization (Expand Search), swarm optimization (Expand Search), whale optimization (Expand Search)
class lead » class lca (Expand Search), class left (Expand Search)
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Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat.
Published 2025“…<br>The consistency of the results across different kernels demonstrates that the information contained in the habitat, by itself, leads to a very simple optimal decision rule (mostly the prediction of the most frequent class per habitat), which cannot be improved solely by model adjustments. …”
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Supplementary Material 8
Published 2025“…In AMR studies, datasets often contain more susceptible isolates than resistant ones, leading to biased model performance. SMOTE overcomes this issue by generating synthetic samples of the minority class (resistant isolates) through interpolation rather than simple duplication, thereby improving model generalization.…”
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Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles
Published 2025“…</p><p dir="ltr"><b>Applications and Model Compatibility:</b></p><p dir="ltr">The dataset is optimized for use in supervised learning workflows and has been tested with algorithms such as:</p><p dir="ltr">Gradient Boosting Machines (GBM),</p><p dir="ltr">Support Vector Machines (SVM-RBF),</p><p dir="ltr">Random Forests, and</p><p dir="ltr">Principal Component Analysis (PCA) for feature reduction.…”