Table 5_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.xlsx حسب 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 حسب 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 حسب 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. …"

CEC2017 test function test results. حسب Tengfei Ma (597633)

"…During experimental evaluation, the efficiency of OP-ZOA was verified using the CEC2017 test functions, demonstrating superior performance compared to seven recently proposed meta-heuristic algorithms (Bloodsucking Leech Algorithm (BSLO), Parrot Optimization Algorithm (PO), Polar Lights Algorithm (PLO), Red-tailed Hawk Optimization Algorithm (RTH), Bitterling Fish Optimization Algorithm (BFO), Spider Wasp Optimization Algorithm (SWO) and Zebra Optimization Algorithm (ZOA)). …"

F1-scores of anomaly detection algorithms. حسب GaoXiang Zhao (21499525)

"…Empirical evaluations conducted on multiple benchmark datasets demonstrate that the proposed method outperforms classical anomaly detection algorithms while surpassing conventional model averaging techniques based on minimizing standard loss functions. …"

Simulation settings of rMAPPO algorithm. حسب Jianbin Zheng (587000)

"…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. The effectiveness of the proposed method is then verified on both the physical work cell for riveting and welding and its digital twin platform, and it is compared with other baseline multi-agent reinforcement learning methods (MAPPO, MADDPG, and MASAC). …"

Mathematical expressions, weight functions, domains, and orthogonality conditions of various orthogonal polynomials. حسب Abeer Aljohani (18497914)

الموضوعات:

Data Sheet 1_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.docx حسب 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. …"

Uncertainty Based Machine Learning-DFT Hybrid Framework for Accelerating Geometry Optimization حسب Akksay Singh (20176616)

(a) Comparison between SDNN and Traditional Methods. The horizontal axis represents the prediction horizon, while the vertical axis denotes computation time; red denotes traditiona... حسب Kai Sun (140584)

Temporal analysis of epithelial cells. حسب Yanfeng Xue (465345)

الموضوعات:

RNA sequencing analysis and screening of anoikis-related signature genes. حسب Yanfeng Xue (465345)

الموضوعات:

The gene set related to the “Cytotoxicity” and “Progenitor exhaustion” function of T cells. حسب Yanfeng Xue (465345)

الموضوعات:

Predicting CO₂ Solubility in Diverse Ionic Liquids: A Data-Driven Approach Using Machine Learning Algorithms حسب Zahra Bastami (21474755)

Predicting CO₂ Solubility in Diverse Ionic Liquids: A Data-Driven Approach Using Machine Learning Algorithms حسب Zahra Bastami (21474755)

Accuracy of the support vector machines for different proportion of test samples and different length of nodes used for training. حسب Abeer Aljohani (18497914)

الموضوعات:

Machine learning from 21 gly - DEGs filter core gene. حسب Ziyang Liu (242055)

الموضوعات:

If datasets are small and/or noisy, linear-regression-based algorithms for identifying functional groups outperform more complex versions. حسب Yuanchen Zhao (12905580)

"…Each algorithm return a set of coarsened <i>variables</i> (a grouping of species into three groups) and a <i>model</i> that uses these variables to predict the function. …"

Supplemental files to the study "Limitations of Current Machine-Learning Models in Predicting Enzymatic Functions for Uncharacterized Proteins" حسب Valerie de Crecy-Lagard (12823436)

"…An open question is the ability of machine-learning approaches to predict enzymatic functions unseen in the training sets. …"

Table 5_Feature genes identification and immune infiltration assessment in abdominal aortic aneurysm using WGCNA and machine learning algorithms.xls حسب Ming Xie (420493)

"…By intersecting the result of 3 machine learning algorithms and WGCNA, 3 feature genes were identified, including MRAP2, PPP1R14A, and PLN genes. …"