Search alternatives:
property optimization » process optimization (Expand Search), policy optimization (Expand Search), robust optimization (Expand Search)
guided optimization » based optimization (Expand Search), model optimization (Expand Search)
data property » taste property (Expand Search), peat property (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
binary ct » binary _ (Expand Search), binary b (Expand Search)
Showing 1 - 8 results of 8 for search '(( binary ct guided optimization algorithm ) OR ( binary data property optimization algorithm ))*', query time: 0.39s Refine Results
  1. 1
    Datasets and their properties.

    Datasets and their properties. by Olaide N. Oyelade (14047002)

    Published 2023
    Save to List
    Saved in:
  2. 2
    RMSE on the test data when fitting (logistic) quadratic models to binary data across increasing measurement error values .

    RMSE on the test data when fitting (logistic) quadratic models to binary data across increasing measurement error values . by Jakub Stoklosa (3315042)

    Published 2023
    Save to List
    Saved in:
  3. 3
    Data_Sheet_1_A Global Optimizer for Nanoclusters.PDF

    Data_Sheet_1_A Global Optimizer for Nanoclusters.PDF by Maya Khatun (7437011)

    Published 2019
    Save to List
    Saved in:
  4. 4
    Fig 1 -

    Fig 1 - by Jakub Stoklosa (3315042)

    Published 2023
    Save to List
    Saved in:
  5. 5
    Predicting Thermal Decomposition Temperature of Binary Imidazolium Ionic Liquid Mixtures from Molecular Structures

    Predicting Thermal Decomposition Temperature of Binary Imidazolium Ionic Liquid Mixtures from Molecular Structures by Hongpeng He (348094)

    Published 2021
    “…The subset of optimal descriptors was screened by combining the genetic algorithm with the multiple linear regression method. …”
    Save to List
    Saved in:
  6. 6
    Supplementary Material for: Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes

    Supplementary Material for: Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes by Yu Y. (3096192)

    Published 2022
    “…Our estimate of m is the maximizer of a marginal likelihood obtained by integrating the latent log-ORs out of the joint distribution of the parameters and observed data. We consider two approximate approaches to maximizing the marginal likelihood: (i) a Monte Carlo EM algorithm (MCEM) and (ii) a Laplace approximation (LA) to each integral, followed by derivative-free optimization of the approximation. …”
    Save to List
    Saved in:
  7. 7
    Variable Selection with Multiply-Imputed Datasets: Choosing Between Stacked and Grouped Methods

    Variable Selection with Multiply-Imputed Datasets: Choosing Between Stacked and Grouped Methods by Jiacong Du (12035845)

    Published 2022
    “…Building on existing work, we (i) derive and implement efficient cyclic coordinate descent and majorization-minimization optimization algorithms for continuous and binary outcome data, (ii) incorporate adaptive shrinkage penalties, (iii) compare these methods through simulation, and (iv) develop an R package <i>miselect</i>. …”
    Save to List
    Saved in:
  8. 8
    Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles

    Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles by Soham Savarkar (21811825)

    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.…”
    Save to List
    Saved in:

Search Tools: