Showing 1 - 20 results of 53 for search '(( library based small optimization algorithm ) OR ( binary based sample optimization algorithm ))', query time: 1.75s Refine Results
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    ROC curve for binary classification. by Nicodemus Songose Awarayi (18414494)

    Published 2024
    “…Specifically, an image enhancement algorithm based on histogram equalization and bilateral filtering techniques was deployed to reduce noise and enhance the quality of the images. …”
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    Confusion matrix for binary classification. by Nicodemus Songose Awarayi (18414494)

    Published 2024
    “…Specifically, an image enhancement algorithm based on histogram equalization and bilateral filtering techniques was deployed to reduce noise and enhance the quality of the images. …”
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    Identification and quantitation of clinically relevant microbes in patient samples: Comparison of three k-mer based classifiers for speed, accuracy, and sensitivity by George S. Watts (7962206)

    Published 2019
    “…We tested the accuracy, sensitivity, and resource requirements of three top metagenomic taxonomic classifiers that use fast k-mer based algorithms: Centrifuge, CLARK, and KrakenUniq. …”
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    iRaPCA and SOMoC: Development and Validation of Web Applications for New Approaches for the Clustering of Small Molecules by Denis N. Prada Gori (5798651)

    Published 2022
    “…Here, two open-source in-house methodologies for clustering of small molecules are presented: iterative Random subspace Principal Component Analysis clustering (iRaPCA), an iterative approach based on feature bagging, dimensionality reduction, and K-means optimization; and Silhouette Optimized Molecular Clustering (SOMoC), which combines molecular fingerprints with the Uniform Manifold Approximation and Projection (UMAP) and Gaussian Mixture Model algorithm (GMM). …”
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    iRaPCA and SOMoC: Development and Validation of Web Applications for New Approaches for the Clustering of Small Molecules by Denis N. Prada Gori (5798651)

    Published 2022
    “…Here, two open-source in-house methodologies for clustering of small molecules are presented: iterative Random subspace Principal Component Analysis clustering (iRaPCA), an iterative approach based on feature bagging, dimensionality reduction, and K-means optimization; and Silhouette Optimized Molecular Clustering (SOMoC), which combines molecular fingerprints with the Uniform Manifold Approximation and Projection (UMAP) and Gaussian Mixture Model algorithm (GMM). …”
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    iRaPCA and SOMoC: Development and Validation of Web Applications for New Approaches for the Clustering of Small Molecules by Denis N. Prada Gori (5798651)

    Published 2022
    “…Here, two open-source in-house methodologies for clustering of small molecules are presented: iterative Random subspace Principal Component Analysis clustering (iRaPCA), an iterative approach based on feature bagging, dimensionality reduction, and K-means optimization; and Silhouette Optimized Molecular Clustering (SOMoC), which combines molecular fingerprints with the Uniform Manifold Approximation and Projection (UMAP) and Gaussian Mixture Model algorithm (GMM). …”
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    Triplet Matching for Estimating Causal Effects With Three Treatment Arms: A Comparative Study of Mortality by Trauma Center Level by Giovanni Nattino (561797)

    Published 2021
    “…Our algorithm outperforms the nearest neighbor algorithm and is shown to produce matched samples with total distance no larger than twice the optimal distance. …”
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    Testing results for classifying AD, MCI and NC. by Nicodemus Songose Awarayi (18414494)

    Published 2024
    “…Specifically, an image enhancement algorithm based on histogram equalization and bilateral filtering techniques was deployed to reduce noise and enhance the quality of the images. …”
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    Summary of existing CNN models. by Nicodemus Songose Awarayi (18414494)

    Published 2024
    “…Specifically, an image enhancement algorithm based on histogram equalization and bilateral filtering techniques was deployed to reduce noise and enhance the quality of the images. …”
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    Parameter settings. by Yang Cao (53545)

    Published 2024
    “…<div><p>Differential Evolution (DE) is widely recognized as a highly effective evolutionary algorithm for global optimization. It has proven its efficacy in tackling diverse problems across various fields and real-world applications. …”
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    Acceleration of Inverse Molecular Design by Using Predictive Techniques by Jos L. Teunissen (1911856)

    Published 2019
    “…This study addresses one of the most important drawbacks inherently related to molecular searches in chemical compound space by greedy algorithms such as Best First Search and Genetic Algorithm, i.e., the large computational cost required to optimize one or more quantum-chemical properties. …”