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Showing 1 - 5 results of 5 for search 'binary training robust estimation algorithm', query time: 0.28s Refine Results
  1. 1
    Individual Transition Label Noise Logistic Regression in Binary Classification for Incorrectly Labeled Data

    Individual Transition Label Noise Logistic Regression in Binary Classification for Incorrectly Labeled Data by Seokho Lee (10088)

    Published 2021
    “…<p>We consider a binary classification problem in the case where some observations in the training data are incorrectly labeled. …”
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  2. 2
    DataSheet_1_Preoperatively Estimating the Malignant Potential of Mediastinal Lymph Nodes: A Pilot Study Toward Establishing a Robust Radiomics Model Based on Contrast-Enhanced CT Imaging.pdf

    DataSheet_1_Preoperatively Estimating the Malignant Potential of Mediastinal Lymph Nodes: A Pilot Study Toward Establishing a Robust Radiomics Model Based on Contrast-Enhanced CT I... by Mengshi Dong (5181833)

    Published 2021
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  3. 3
    QSAR model for predicting neuraminidase inhibitors of influenza A viruses (H1N1) based on adaptive grasshopper optimization algorithm

    QSAR model for predicting neuraminidase inhibitors of influenza A viruses (H1N1) based on adaptive grasshopper optimization algorithm by Z.Y. Algamal (5547620)

    Published 2020
    “…Obtaining a reliable QSAR model with few descriptors is an essential procedure in chemometrics. The binary grasshopper optimization algorithm (BGOA) is a new meta-heuristic optimization algorithm, which has been used successfully to perform feature selection. …”
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  4. 4
    Comparisons of prediction of phenotypes by the microbiome.

    Comparisons of prediction of phenotypes by the microbiome. by Daphna Rothschild (561439)

    Published 2022
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  5. 5
    An AI-based Ecosystem for Real-time Gravitational Wave Analyses

    An AI-based Ecosystem for Real-time Gravitational Wave Analyses by Erik Katsavounidis (19369348)

    Published 2024
    “…These libraries enhance efficiency and AI model robustness in the context of a broad range of gravitational wave analyses with an emphasis on real-time application, scalability to heterogeneous computing resources, and streamlining the training to deployment cycles for machine learning models. …”
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