Reproducing kernel-based semiparametric functional smoothed score estimation with binary responses حسب Meichen Liu (8168148)

Random forest model performs better than support vector machine algorithms and when it primarily uses spontaneous photopic ERG of 60-s duration in humans. حسب Ramsés Noguez Imm (6658637)

Table 1_A comparative analysis of binary and multi-class classification machine learning algorithms to detect current frailty status using the English longitudinal study of ageing... حسب Charmayne Mary Lee Hughes (12959972)

"…</p>Conclusion<p>Machine learning algorithms show promise for the detection of current frailty status, particularly in binary classification. …"

Multicategory Angle-Based Learning for Estimating Optimal Dynamic Treatment Regimes With Censored Data حسب Fei Xue (24567)

"…Specifically, the proposed method obtains the optimal DTR via integrating estimations of decision rules at multiple stages into a single multicategory classification algorithm without imposing additional constraints, which is also more computationally efficient and robust. …"

Evaluation of Binary Classifiers for Asymptotically Dependent and Independent Extremes حسب Juliette Legrand (21771740)

Calibration curves for the test set of four models. حسب Meng Cao (105914)

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SHAP bar plot. حسب Meng Cao (105914)

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ROC curves for the test set of four models. حسب Meng Cao (105914)

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Display of the web prediction interface. حسب Meng Cao (105914)

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Sample screening flowchart. حسب Meng Cao (105914)

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Descriptive statistics for variables. حسب Meng Cao (105914)

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SHAP summary plot. حسب Meng Cao (105914)

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Performance metrics of the models on the training and test set. حسب Meng Cao (105914)

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

Spontaneous ERG-based random forest model discriminates control and disease cases in rodent models of obesity and type 1 diabetes and predicts disease evolution in the type 1 diabe... حسب Ramsés Noguez Imm (6658637)

Comparison with previous studies. حسب Ji Seung Ryu (16187857)

"…Three datasets were used for the experiment: the male, female, and entire dataset. A cutoff for binary classification was defined as the meaningful as a screening test (<132 g/m² vs. ≥132 g/m², <109 g/m² vs. ≥109 g/m²). …"

Dataset characteristics. حسب Ji Seung Ryu (16187857)

"…Three datasets were used for the experiment: the male, female, and entire dataset. A cutoff for binary classification was defined as the meaningful as a screening test (<132 g/m² vs. ≥132 g/m², <109 g/m² vs. ≥109 g/m²). …"

Acronym table. حسب Ji Seung Ryu (16187857)

"…Three datasets were used for the experiment: the male, female, and entire dataset. A cutoff for binary classification was defined as the meaningful as a screening test (<132 g/m² vs. ≥132 g/m², <109 g/m² vs. ≥109 g/m²). …"

Fairness in Machine Learning: A Review for Statisticians حسب Xianwen He (22529252)

"…We organize these fairness-enhancing mechanisms into three categories—pre-processing, in-processing, and post-processing—corresponding to different stages of the machine learning lifecycle and varying levels of access to the underlying algorithm. The discussion focuses on fairness in binary classification models using numerical tabular data, which serve as a foundation for addressing fairness in more complex algorithms. …"

Table_10_Artificial Intelligence-Enabled ECG Algorithm for the Prediction of Coronary Artery Calcification.xlsx حسب Changho Han (1309563)