Classical Predictive Coding for motion processing. حسب Elnaz Nemati (21402730)

الموضوعات:

Effects of noise level and surround suppression threshold on model convergence time in the RDK task, experiment III. حسب Elnaz Nemati (21402730)

الموضوعات:

Relevant Parameters. حسب Dongyan Wang (195482)

The GOR4 and SOPMA algorithm findings. حسب Ahmad Abdullah Mahdeen (19704401)

Results of different pheromone evaporation rates in the IACO algorithm. حسب Pengfei Huang (552512)

XGBoost odor prediction model: finding the structure-odor relationship of odorant molecules using the extreme gradient boosting algorithm حسب Pankaj Tyagi (20147683)

Main code. حسب Jingguo Bi (21439766)

Key Findings and Methodologies. حسب Carlos M. Ardila (19996060)

CatBoost algorithm structure to predict clinical outcome. حسب Andrew McDonald (2307400)

الموضوعات: "…provide interpretable predictions…"

Explanation and Values of Relevant Parameters in the Case. حسب Chen Hao (352436)

Data Sheet 1_Predicting place of delivery choice among childbearing women in East Africa: a comparative analysis of advanced machine learning techniques.pdf حسب Habtamu Setegn Ngusie (12178327)

"…</p>Result<p>The prevalence of health facility delivery in East Africa was found to be 83.71%. The findings showed that the support vector machine (SVM) algorithm and CatBoost performed best in predicting the place of delivery, in which both of those algorithms scored an accuracy of 95% and an AUC of 0.98 after optimized with Bayesian optimization tuning and insignificant difference between them in all comprehensive analysis of metrics performance. …"

Data Sheet 2_Predicting place of delivery choice among childbearing women in East Africa: a comparative analysis of advanced machine learning techniques.pdf حسب Habtamu Setegn Ngusie (12178327)

"…</p>Result<p>The prevalence of health facility delivery in East Africa was found to be 83.71%. The findings showed that the support vector machine (SVM) algorithm and CatBoost performed best in predicting the place of delivery, in which both of those algorithms scored an accuracy of 95% and an AUC of 0.98 after optimized with Bayesian optimization tuning and insignificant difference between them in all comprehensive analysis of metrics performance. …"

Parameters of stimuli used in the study. حسب Elnaz Nemati (21402730)

الموضوعات:

Summary of relevant papers concerning fractional differential equations. حسب Mahmoud Abd El-Hady (20558624)

Prediction performance compared with the CART algorithm. حسب Yixian Wen (12201388)

Relevant data underlying the findings described in manuscript. حسب Lin Qi (128224)

Performance of different models in internal and external validations: ROC, calibration, and DCA curves. حسب Lei Gao (6566)

الموضوعات:

Pseudo-code of large neighborhood search (<i>LNS</i>) algorithm. حسب Jiren CAO (20442214)

Prediction performance compared with random forest algorithm. حسب Yixian Wen (12201388)

The relevant code in the manuscript can be found in the supporting information data file. حسب Xini Fang (20861990)