Search alternatives:
model optimization » codon optimization (Expand Search), global optimization (Expand Search), wolf optimization (Expand Search)
based optimization » whale optimization (Expand Search)
primary data » primary care (Expand Search)
binary data » dietary data (Expand Search)
data model » data models (Expand Search)
data based » data used (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), wolf optimization (Expand Search)
based optimization » whale optimization (Expand Search)
primary data » primary care (Expand Search)
binary data » dietary data (Expand Search)
data model » data models (Expand Search)
data based » data used (Expand Search)
-
41
FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
Published 2024Subjects: -
42
The statistical description of the original data set of the patients (<i>n</i> = 162).
Published 2025Subjects: -
43
Comparison of baseline and hybrid machine learning models in predicting IVF outcomes (%).
Published 2025Subjects: -
44
-
45
The list of parameters of the modified data set for machine learning (<i>n</i> = 162).
Published 2025Subjects: -
46
-
47
Calibration curve of the ABC–LR–RF hybrid model for IVF outcome prediction.
Published 2025Subjects: -
48
ROC and PR–AUC curves of the ABC–LR–RF hybrid model for IVF outcome prediction.
Published 2025Subjects: -
49
DATA.
Published 2025“…These enhancements aim to achieve optimal routing scheduling based on risk information. …”
-
50
Data_Sheet_1_Prediction of patient choice tendency in medical decision-making based on machine learning algorithm.pdf
Published 2023“…Objective<p>Machine learning (ML) algorithms, as an early branch of artificial intelligence technology, can effectively simulate human behavior by training on data from the training set. …”
-
51
Detailed information of benchmark functions.
Published 2024“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”
-
52
Evaluation metrics of the models’ performance.
Published 2024“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”
-
53
Detailed information of datasets.
Published 2024“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”
-
54
Friedman test results.
Published 2024“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”
-
55
Average number of selected features.
Published 2024“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”
-
56
Wilcoxon rank sum test results.
Published 2024“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”
-
57
Wilcoxon rank sum test results.
Published 2024“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”
-
58
Average number of selected features.
Published 2024“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”
-
59
-
60