Showing 61 - 80 results of 143 for search '(( binary image based optimization algorithm ) OR ( library based models optimization algorithm ))', query time: 0.33s Refine Results
  1. 61

    Box plot comparison on instance j30c5e10. by Xiang Tian (4369285)

    Published 2025
    “…Finally, based on a large number of instances and real cases, IPMMPO-CP is compared with 9 representative algorithms and 2 latest CP models. …”
  2. 62

    Presentation_1_Optimization of the k-nearest-neighbors model for summer Arctic Sea ice prediction.pdf by Yongcheng Lin (776525)

    Published 2023
    “…Based on the physical characteristics of summer sea ice, different algorithms are employed to optimize the prediction model. …”
  3. 63

    Presentation_1_Optimization of the k-nearest-neighbors model for summer Arctic Sea ice prediction.pdf by Yongcheng Lin (776525)

    Published 2023
    “…Based on the physical characteristics of summer sea ice, different algorithms are employed to optimize the prediction model. …”
  4. 64

    Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf by Cecilia Lindig-León (7889777)

    Published 2020
    “…And we propose two new multilabel uses of the Common Spatial Pattern (CSP) algorithm to optimize the signal-to-noise ratio, namely MC2CMI and MC2SMI approaches. …”
  5. 65

    PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery by Muzammil Kabier (21028487)

    Published 2025
    “…The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly predictive models for assisting the rationale design of new bioactive compounds, for screening and prioritizing large molecular libraries, and for repurposing new drugs toward new clinical uses. …”
  6. 66

    PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery by Muzammil Kabier (21028487)

    Published 2025
    “…The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly predictive models for assisting the rationale design of new bioactive compounds, for screening and prioritizing large molecular libraries, and for repurposing new drugs toward new clinical uses. …”
  7. 67

    PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery by Muzammil Kabier (21028487)

    Published 2025
    “…The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly predictive models for assisting the rationale design of new bioactive compounds, for screening and prioritizing large molecular libraries, and for repurposing new drugs toward new clinical uses. …”
  8. 68

    PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery by Muzammil Kabier (21028487)

    Published 2025
    “…The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly predictive models for assisting the rationale design of new bioactive compounds, for screening and prioritizing large molecular libraries, and for repurposing new drugs toward new clinical uses. …”
  9. 69

    PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery by Muzammil Kabier (21028487)

    Published 2025
    “…The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly predictive models for assisting the rationale design of new bioactive compounds, for screening and prioritizing large molecular libraries, and for repurposing new drugs toward new clinical uses. …”
  10. 70

    PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery by Muzammil Kabier (21028487)

    Published 2025
    “…The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly predictive models for assisting the rationale design of new bioactive compounds, for screening and prioritizing large molecular libraries, and for repurposing new drugs toward new clinical uses. …”
  11. 71

    PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery by Muzammil Kabier (21028487)

    Published 2025
    “…The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly predictive models for assisting the rationale design of new bioactive compounds, for screening and prioritizing large molecular libraries, and for repurposing new drugs toward new clinical uses. …”
  12. 72

    PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery by Muzammil Kabier (21028487)

    Published 2025
    “…The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly predictive models for assisting the rationale design of new bioactive compounds, for screening and prioritizing large molecular libraries, and for repurposing new drugs toward new clinical uses. …”
  13. 73

    PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery by Muzammil Kabier (21028487)

    Published 2025
    “…The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly predictive models for assisting the rationale design of new bioactive compounds, for screening and prioritizing large molecular libraries, and for repurposing new drugs toward new clinical uses. …”
  14. 74

    PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery by Muzammil Kabier (21028487)

    Published 2025
    “…The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly predictive models for assisting the rationale design of new bioactive compounds, for screening and prioritizing large molecular libraries, and for repurposing new drugs toward new clinical uses. …”
  15. 75

    PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery by Muzammil Kabier (21028487)

    Published 2025
    “…The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly predictive models for assisting the rationale design of new bioactive compounds, for screening and prioritizing large molecular libraries, and for repurposing new drugs toward new clinical uses. …”
  16. 76

    PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery by Muzammil Kabier (21028487)

    Published 2025
    “…The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly predictive models for assisting the rationale design of new bioactive compounds, for screening and prioritizing large molecular libraries, and for repurposing new drugs toward new clinical uses. …”
  17. 77

    SHAP bar plot. by Meng Cao (105914)

    Published 2025
    “…The optimal model was further assessed for predictor importance utilizing the SHAP method and deployed on a web platform using the Streamlit library.…”
  18. 78

    Sample screening flowchart. by Meng Cao (105914)

    Published 2025
    “…The optimal model was further assessed for predictor importance utilizing the SHAP method and deployed on a web platform using the Streamlit library.…”
  19. 79

    Descriptive statistics for variables. by Meng Cao (105914)

    Published 2025
    “…The optimal model was further assessed for predictor importance utilizing the SHAP method and deployed on a web platform using the Streamlit library.…”
  20. 80

    SHAP summary plot. by Meng Cao (105914)

    Published 2025
    “…The optimal model was further assessed for predictor importance utilizing the SHAP method and deployed on a web platform using the Streamlit library.…”