The parameter settings of the RF algorithm after parameter optimization. by Xini Fang (20861990)

Distributions of model parameters mirror differentially expressed ion channel genes. by Daniele Linaro (227790)

Data_Sheet_2_Computational Neural Modeling of Auditory Cortical Receptive Fields.pdf by Jordan D. Chambers (6732224)

Data_Sheet_1_Computational Neural Modeling of Auditory Cortical Receptive Fields.PDF by Jordan D. Chambers (6732224)

Data_Sheet_3_Computational Neural Modeling of Auditory Cortical Receptive Fields.PDF by Jordan D. Chambers (6732224)

Parameter optimization results of the RF model improved by FCM clustering. by Xini Fang (20861990)

S1 Code - by Gaosha Li (20570760)

“…A combination of four machine learning algorithms (XGBoost、Logistic Regression、Random Forest、AdaBoost) was employed to predict NPM recurrence, and the model with the highest Area Under the Curve (AUC) in the test set was selected as the best model. …”

Evaluation metrics of the models’ performance. by Guangwei Liu (181992)

Pseudocode of artificial dragonfly algorithm. by Ghassan Ahmed Ali (17041488)

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Features selected by optimization algorithms. by Afnan M. Alhassan (18349378)

“…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”

Input features. by Nicola Lazzarini (3528197)

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Baseline characteristics of patients in the study cohort. by Nicola Lazzarini (3528197)

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The Hopfield artificial neural network algorithm. by Ghassan Ahmed Ali (17041488)

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Zimbabwe model outputs on actual and optimized 2016 spending and impact by intervention. by Nicole Fraser-Hurt (2636833)

Optimized model prediction performance. by Guang Tu (22054865)

ECE6379_PSOM.zip by Xingpeng Li (11825663)

“…Optimization algorithms that are commonly used to solve these problems will also be covered including linear programming, mixed-integer linear programming, Lagrange relaxation, dynamic programming, branch and bound, and duality theory.…”

Data_Sheet_1_How can age-based vaccine allocation strategies be optimized? A multi-objective optimization framework.ZIP by Hao Wu (65943)

Côte d’Ivoire model outputs on actual and optimized 2016 spending and impact by care delivery platform. by Nicole Fraser-Hurt (2636833)

Table_1_Screening of Long Non-coding RNAs Biomarkers for the Diagnosis of Tuberculosis and Preliminary Construction of a Clinical Diagnosis Model.docx by Juli Chen (12187358)

“…Background<p>Pathogenic testing for tuberculosis (TB) is not yet sufficient for early and differential clinical diagnosis; thus, we investigated the potential of screening long non-coding RNAs (lncRNAs) from human hosts and using machine learning (ML) algorithms combined with electronic health record (EHR) metrics to construct a diagnostic model.…”

Training error and accuracy for all HNN models. by Ghassan Ahmed Ali (17041488)

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