A sample confusion matrix of binary classifier. حسب Eric Komla Anku (17959299)

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

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

An illustrated example of Algorithm 1 (Fig 1). حسب Kathleen M. Jagodnik (10170617)

Link Prediction for Egocentrically Sampled Networks حسب Tianxi Li (8460468)

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

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

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

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

Benchmarking of algorithms for unsupervised clustering of multi-omics data. حسب Polina Suter (11879717)

Modeling Pregnancy Outcomes Through Sequentially Nested Regression Models حسب 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 حسب Paolo Onorati (20461248)

"…We discuss in detail the popular logit case, and we show that, when a logistic regression model is combined with a Gaussian prior, posterior summaries such as cumulants and normalizing constants can easily be obtained through the use of an importance sampling approach, opening the way to straightforward variable selection procedures. …"

Data_Sheet_1_Pneumonia detection by binary classification: classical, quantum, and hybrid approaches for support vector machine (SVM).pdf حسب Sai Sakunthala Guddanti (17739363)

"…A support vector machine (SVM) is attractive because binary classification can be represented as an optimization problem, in particular as a Quadratic Unconstrained Binary Optimization (QUBO) model, which, in turn, maps naturally to an Ising model, thereby making annealing—classical, quantum, and hybrid—an attractive approach to explore. …"

MCLP_quantum_annealer_V0.5 حسب Anonymous Anonymous (4854526)

"…Theoretical and applied experiments are conducted using four solvers: QBSolv, D-Wave Hybrid binary quadratic model 2, D-Wave Advantage system 4.1, and Gurobi. …"

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

UNet++ type architecture [68] used for all the problems in this paper. حسب Dylan D. Ray (3741823)

Interpretability analysis. حسب Michela C. Massi (14599915)