يعرض 1 - 20 نتائج من 12,784 نتيجة بحث عن '(((( algorithms linear function ) OR ( algorithm 1 function ))) OR ( algorithm python function ))', وقت الاستعلام: 0.63s تنقيح النتائج
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    Linear-regression-based algorithms succeed at identifying the correct functional groups in synthetic data, and multi-group algorithms recover more information. حسب Yuanchen Zhao (12905580)

    منشور في 2024
    "…<p>(A), (B) Algorithm performance, evaluated over 50 simulated datasets generated as described in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1012590#pcbi.1012590.g001" target="_blank">Fig 1</a> with <i>N</i> = 3 true groups, 900 samples and 10% simulated measurement noise. …"
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    Parameters of trained algorithms. حسب Swathi Anil (17382903)

    منشور في 2025
    الموضوعات:
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    EFGs: A Complete and Accurate Implementation of Ertl’s Functional Group Detection Algorithm in RDKit حسب Gonzalo Colmenarejo (650249)

    منشور في 2025
    "…For a RDKit molecule, it provides (i) a PNG binary string with an image of the molecule with color-highlighted functional groups; (ii) a list of sets of atom indices (idx), each set corresponding to a functional group; (iii) a list of pseudo-SMILES canonicalized strings for the full functional groups; and (iv) a list of RDKit labeled mol objects, one for each full functional group. …"
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    Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results حسب Se-Hee Jo (20554623)

    منشور في 2025
    "…This algorithm conducts a series of procedures: (1) fragmentation of the molecules into functional groups from SMILES, (2) calculation of activity coefficients under predetermined temperature and mole fraction conditions by employing universal quasi-chemical functional group activity coefficient (UNIFAC) model, and (3) regression of NRTL model parameters by employing UNIFAC model simulation results in the differential evolution algorithm (DEA) and Nelder–Mead method (NMM). …"
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    <b>Opti2Phase</b>: Python scripts for two-stage focal reducer حسب Morgan Najera (21540776)

    منشور في 2025
    "…</li></ul><p dir="ltr">The scripts rely on the following Python packages. Where available, repository links are provided:</p><ol><li><b>NumPy</b>, version 1.22.1</li><li><b>SciPy</b>, version 1.7.3</li><li><b>PyGAD</b>, version 3.0.1 — https://pygad.readthedocs.io/en/latest/#</li><li><b>bees-algorithm</b>, version 1.0.2 — https://pypi.org/project/bees-algorithm</li><li><b>KrakenOS</b>, version 1.0.0.19 — https://github.com/Garchupiter/Kraken-Optical-Simulator</li><li><b>matplotlib</b>, version 3.5.2</li></ol><p dir="ltr">All scripts are modular and organized to reflect the design stages described in the manuscript.…"
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    If datasets are small and/or noisy, linear-regression-based algorithms for identifying functional groups outperform more complex versions. حسب Yuanchen Zhao (12905580)

    منشور في 2024
    "…Both versions are evaluated on the same synthetic datasets with a 3-group ground truth. Each algorithm return a set of coarsened <i>variables</i> (a grouping of species into three groups) and a <i>model</i> that uses these variables to predict the function. …"
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    An expectation-maximization algorithm for finding noninvadable stationary states. حسب Robert Marsland (8616483)

    منشور في 2020
    "…<i>(b)</i> Metabolic byproducts move the relevant unperturbed state from <b>R</b><sup>0</sup> (gray ‘x’) to (black ‘x’), which is itself a function of the current environmental conditions. …"
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