Search alternatives:
features selection » feature selection (Expand Search), natural selection (Expand Search)
selection decrease » reduction decreased (Expand Search)
marked decrease » marked increase (Expand Search)
large decrease » larger decrease (Expand Search), large increases (Expand Search), large degree (Expand Search)
features selection » feature selection (Expand Search), natural selection (Expand Search)
selection decrease » reduction decreased (Expand Search)
marked decrease » marked increase (Expand Search)
large decrease » larger decrease (Expand Search), large increases (Expand Search), large degree (Expand Search)
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The wetting feature of compound solutions.
Published 2025“…We prepared the blends of these five surfactants, each with a mass fraction of 0.5 wt%, in a 1:1 ratio, resulting in 10 blended solutions. We measured the performance of these solutions and revealed that the AES + AEO-9 blend demonstrated a significant synergistic effect, markedly enhancing the capture efficiency of water for lignite dust.…”
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Feature selection and feature importance ranking.
Published 2025“…<p>A: The flowchart of feature selection based on the RFE algorithm. B: The RFE results reflect the changes in the average R2 of the 20-fold pair-level cross-validation as the number of RFE rounds increases and the number of features decreases. …”
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<b>The loss of insulin-positive cell clusters precedes the decrease of islet frequency and beta cell area in type 1 diabetes</b>
Published 2025“…Age-corrected data revealed decreased islet frequency and increased inter-islet distances in the type 1 diabetes pancreas. …”
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Number of features selected.
Published 2025“…In this paper, a Lean-based hybrid Intrusion Detection framework using Particle Swarm Optimization and Genetic Algorithm (PSO-GA) to select the features and Extreme Learning Machine and Bootstrap Aggregation (ELM-BA) to classify the features is introduced. …”
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Some examples of selected Chinese characters.
Published 2025“…Our model shows clear enhancements in structural accuracy (SSIM improved to 0.91), pixel-level fidelity (RMSE reduced to 2.68), perceptual quality aligned with human vision (LPIPS reduced to 0.07), and stylistic realism (FID decreased to 13.87). It reduces the model size to 100M parameters, cuts training time to just 1.3 hours, and lowers inference time to only 21 minutes. …”
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Correlation heatmap of selected features.
Published 2025“…In this paper, a Lean-based hybrid Intrusion Detection framework using Particle Swarm Optimization and Genetic Algorithm (PSO-GA) to select the features and Extreme Learning Machine and Bootstrap Aggregation (ELM-BA) to classify the features is introduced. …”