Performance of the ceRNAR package using synthetic data with randomly selected correlation values from 0.8 to 0.9. by Yi-Wen Hsiao (13767916)

Performance of the ceRNAR package in five scenarios under the complete version using synthetic data with randomly selected correlation values from 0.3 to 0.9. by Yi-Wen Hsiao (13767916)

Performance of the ceRNAR package in five scenarios under the complete version using synthetic data with randomly selected correlation values from 0.5 to 0.7. by Yi-Wen Hsiao (13767916)

Performance of the ceRNAR package in five scenarios under the complete version using synthetic data with randomly selected correlation values from 0.3 to 0.4. by Yi-Wen Hsiao (13767916)

The workflow of SCARS-Logistic algorithm. by Maryam Sadiq (7046903)

The scheme of CARS-Logistic algorithm. by Maryam Sadiq (7046903)

Smaller gene set of DFC was selected by a unique selection criterion. by Takeru Fujii (11731550)

The basic concept of our idea is illustrated graphically. by Yi-Wen Hsiao (13767916)

<i>hi</i>PRS algorithm process flow. by Michela C. Massi (14599915)

Bayesian variable selection in distributed lag models: a focus on binary quantile and count data regressions by Daniel Dempsey (11805621)

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

The illustration depicts our CQ-CNN architecture for binary image classification. by Mominul Islam (3513758)

Modeling Pregnancy Outcomes Through Sequentially Nested Regression Models by Xuan Bi (3096897)

“…Our approach explicitly bridges the connections across nested outcomes through computationally easy algorithms and enjoys theoretical guarantee of estimation and variable selection. …”

An Extension of the Unified Skew-Normal Family of Distributions and its Application to Bayesian Binary Regression by Paolo Onorati (20461248)

“…For more general prior distributions, the proposed methodology is based on a simple Gibbs sampler algorithm. We also claim that, in the <math><mrow><mi>p</mi><mo>></mo><mi>n</mi></mrow></math> case, our proposal presents better performances—both in terms of mixing and accuracy—compared to the existing methods.…”

Causal Inference Under Outcome-Based Sampling with Monotonicity Assumptions by Sung Jae Jun (17309092)

Parameter settings. by Yang Cao (53545)

“…Finally, the paper incorporates the sampling concept of elite individuals from the Estimation of Distribution Algorithm (EDA) to regenerate new solutions through the selection process in DE. …”

Flowchart scheme of the ML-based model. by Noshaba Qasmi (20405009)

Illustration of the workflow combining BayesFlow with missing data encoding. by Zijian Wang (481291)

Table_1_bSRWPSO-FKNN: A boosted PSO with fuzzy K-nearest neighbor classifier for predicting atopic dermatitis disease.docx by Yupeng Li (507508)

“…In bSRWPSO-FKNN, the core of which is to optimize the classification performance of FKNN through binary SRWPSO.…”

Table_1_Prediction of spherical equivalent difference before and after cycloplegia in school-age children with machine learning algorithms.DOCX by Bei Du (12545461)

“…Random cluster sampling was used to select 2,467 students aged 6–18 years. …”