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

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)

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

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

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

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. …"

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

Parameter settings. حسب 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. …"

Supplementary file 1_Comparative evaluation of fast-learning classification algorithms for urban forest tree species identification using EO-1 hyperion hyperspectral imagery.docx حسب Veera Narayana Balabathina (22518524)

"…This study focuses on developing an efficient classification framework for species-level tree mapping in the Hauz Khas Urban Forest, New Delhi, India, using EO-1 Hyperion hyperspectral imagery.</p>Methods<p>Thirteen supervised classification algorithms were comparatively evaluated, encompassing traditional spectral/statistical classifiers—Maximum Likelihood, Mahalanobis Distance, Minimum Distance, Parallelepiped, Spectral Angle Mapper (SAM), Spectral Information Divergence (SID), and Binary Encoding—and machine learning algorithms including Decision Tree (DT), K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Random Forest (RF), and Artificial Neural Network (ANN). …"

Data_Sheet_1_Alzheimer’s Disease Diagnosis and Biomarker Analysis Using Resting-State Functional MRI Functional Brain Network With Multi-Measures Features and Hippocampal Subfield... حسب Uttam Khatri (12689072)

"…Similarly, from sMRI, we calculated the hippocampal subfield and amygdala nuclei volume using Freesurfer (version 6). Finally, we implemented and compared the different feature selection algorithms to integrate the structural features, brain networks, and voxel features to optimize the diagnostic identifications of AD using support vector machine (SVM) classifiers. …"

Example depiction of the autoML process. حسب Cynthia Lokker (3813832)

"…As the dataset is unbalanced, with more articles that do not meet the criteria for rigor, we used the unbalanced dataset and over- and under-sampled datasets. …"

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

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

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

"…<p>We study causal inference under case-control and case-population sampling. Specifically, we focus on the binary-outcome and binary-treatment case, where the parameters of interest are causal relative and attributable risks defined via the potential outcome framework. …"

Table 1_Provider fidelity in tuberculosis screening practices among adolescents and adults living with HIV in public health facilities in Tanzania: a cross-sectional evaluation.doc... حسب Lucas L. Shilugu (22644302)

"…Simple random and systematic sampling methods were employed to select the records and sessions, respectively. …"

Table 2_Provider fidelity in tuberculosis screening practices among adolescents and adults living with HIV in public health facilities in Tanzania: a cross-sectional evaluation.doc... حسب Lucas L. Shilugu (22644302)

"…Simple random and systematic sampling methods were employed to select the records and sessions, respectively. …"

Super.Complex identifies likely protein complexes within a PPI network using a distributed supervised AutoML method. حسب Meghana Venkata Palukuri (11890672)