Multiple collinearity diagnosis results. حسب Peiwen Zhang (1863202)

Candidate predictor variables included in the initial parameter selection. حسب Hamid Ghanbari (6821096)

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Figure 1. TCRD knowledge graphs concept and overview of the meta-path-XGBoost algorithm, MPxgb(AD), and workflow. حسب Jessica Binder (11748254)

AI-Powered Knowledge Base Enables Transparent Prediction of Nanozyme Multiple Catalytic Activity حسب Julia Razlivina (18605897)

"…For the first time, we enable the prediction of multiple catalytic activities of nanozymes by training an ensemble learning algorithm achieving <i>R</i>² = 0.75 for the Michaelis–Menten constant and <i>R</i>² = 0.77 for the maximum velocity on unseen test data. …"

Model selection for each clustering algorithm considered. حسب Luan Carlos de Sena Monteiro Ozelim (16914117)

الموضوعات:

Single-cell based multiple instance learning predicts AML genetic subtypes with high accuracy and identifies clinically relevant cells. حسب Matthias Hehr (14797745)

Validation of Acetylcholinesterase Inhibition Machine Learning Models for Multiple Species حسب Patricia A. Vignaux (6911525)

الموضوعات:

diaPASEF-Powered Chemoproteomics Enables Deep Kinome Interaction Profiling حسب Kathryn Woods (4689739)

diaPASEF-Powered Chemoproteomics Enables Deep Kinome Interaction Profiling حسب Kathryn Woods (4689739)

diaPASEF-Powered Chemoproteomics Enables Deep Kinome Interaction Profiling حسب Kathryn Woods (4689739)

Fusion outcomes for select frames in the INO dataset. حسب Yandong Liu (11893664)

الموضوعات:

Fusion outcomes for select frames in the BEPMS dataset. حسب Yandong Liu (11893664)

الموضوعات:

Fusion outcomes for select frames in the OTCBVS dataset. حسب Yandong Liu (11893664)

الموضوعات:

Comparison of methodologies in scheme selection. حسب Yixuan Lu (9987980)

"…Finally, the comprehensive scores of alternative schemes are computed using the grey-fuzzy evaluation method to enable decision-making in scheme selection. Cloud model, ELECTRE-II, and VIKOR methodologies were utilized for the comparison of results. …"

Variable selection by RFE. حسب Xiaoli Shen (2208601)

"…<div><p>This study aimed to develop models for predicting the 30-day mortality of sepsis-associated delirium (SAD) by multiple machine learning (ML) algorithms. …"

Prediction intervals of probabilities of failure considering that the input variables are linearly scaled Beta(1,1), i.e., uniform distribution over the interval, according to thei... حسب Luan Carlos de Sena Monteiro Ozelim (16914117)

الموضوعات:

Prediction intervals of probabilities of failure considering that the input variables are linearly scaled Beta(2,2), i.e., the center of mass of the distribution at the center of t... حسب Luan Carlos de Sena Monteiro Ozelim (16914117)

الموضوعات:

Prediction intervals of probabilities of failure considering that the input variables are linearly scaled Beta(5,2), i.e., the center of mass of the distribution closer to the righ... حسب Luan Carlos de Sena Monteiro Ozelim (16914117)

الموضوعات:

Prediction intervals of probabilities of failure considering that the input variables are linearly scaled Beta(2,5), i.e., the center of mass of the distribution closer to the left... حسب Luan Carlos de Sena Monteiro Ozelim (16914117)

الموضوعات:

The workflow of Algorithm 2 with the example in حسب Badhan Das (7434362)