Table 1_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.xlsx by Jingjing Chen (293564)

“…A multi-algorithm machine learning framework was employed to optimize predictive performance, with model interpretability achieved through SHapley Additive exPlanations and diagnostic accuracy validated by receiver operating characteristic curves. …”

Table 4_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.xlsx by Jingjing Chen (293564)

“…A multi-algorithm machine learning framework was employed to optimize predictive performance, with model interpretability achieved through SHapley Additive exPlanations and diagnostic accuracy validated by receiver operating characteristic curves. …”

Table 5_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.xlsx by Jingjing Chen (293564)

“…A multi-algorithm machine learning framework was employed to optimize predictive performance, with model interpretability achieved through SHapley Additive exPlanations and diagnostic accuracy validated by receiver operating characteristic curves. …”

Table 2_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.xlsx by Jingjing Chen (293564)

“…A multi-algorithm machine learning framework was employed to optimize predictive performance, with model interpretability achieved through SHapley Additive exPlanations and diagnostic accuracy validated by receiver operating characteristic curves. …”

Table 3_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.xlsx by Jingjing Chen (293564)

“…A multi-algorithm machine learning framework was employed to optimize predictive performance, with model interpretability achieved through SHapley Additive exPlanations and diagnostic accuracy validated by receiver operating characteristic curves. …”

Flow chart of adaptive network control algorithm to predict the amount of frost. by Bo Yu (241082)

Benchmark functions. by Mingjun Li (178925)

Subjects:

The one-tailed precision for the algorithm as a function of predicted week for the three scenarios and two confidence limits (68% and 95%). by David Harvey (405930)

The two-tailed precision for the algorithm as a function of predicted week for the three scenarios and two confidence intervals (68% and 95%). by David Harvey (405930)

“…<p>The two-tailed precision for the algorithm as a function of predicted week for the three scenarios and two confidence intervals (68% and 95%).…”

Predicted body weights (kg) as a function of time (age in weeks) obtained from MARS algorithm and Gompertz model. by Turgay Şengül (12801990)

“…<p>Predicted body weights (kg) as a function of time (age in weeks) obtained from MARS algorithm and Gompertz model.…”

Data Sheet 1_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.docx by Jingjing Chen (293564)

“…A multi-algorithm machine learning framework was employed to optimize predictive performance, with model interpretability achieved through SHapley Additive exPlanations and diagnostic accuracy validated by receiver operating characteristic curves. …”

The convergence curve of each optimization algorithm under the test function. by Hao Yang (328526)

Box plot of the ADGWDTO and competing algorithms for the seven benchmark functions. by El-Sayed M. El-kenawy (14581088)

Description of the 30 IEEE CEC 2014 benchmark functions. by Qiong Wu (84327)

Predictive capability of the models. by Tuan Anh Pham (1346049)

Subjects:

Pipeline of the interactor algorithm. by Jose Cleydson F. Silva (8685594)

List of ageing-associated genes (STRING identifier and corresponding gene symbol) within imputed genes based on the JenAge Ageing Factor Database for each tissue (brain and liver)... by Konstantina Charmpi (9901053)

Subjects:

Classification thresholds and prediction algorithms for novel PGx variants. by Ewa Goljan (3463487)

Crop yield prediction accuracy using different ML algorithms. by Gourab Saha (8987405)

Subjects:

Test functions. by Huazan Liu (9137461)

Subjects: