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Hace 17 horas · Machine learning algorithms have proven to be practical in a wide range of applications. Many studies have been conducted on the operational energy consumption and thermal comfort of radiant floor systems. This paper conducts a case study in a self-designed experimental setup that combines radiant floor and fan coil cooling (RFCFC) and develops a data monitoring system as a source of ...
Hace 4 días · Federated learning (FL)-based fault diagnosis is being widely developed. However, most of the existing FL methods may suffer from two drawbacks: 1) they are limited to a single diagnosis task, and this may be insufficient when comprehensive health status information is needed and 2) most of them work offline, thus neglecting the useful information contained in newly collected operation data ...
Hace 3 días · This study proposes to examine various machine learning models to predict a student’s performance in a specific course and determine the likelihood of the student passing or failing. With these predictions, the university can intervene early, providing students with support, advice, suggestions, and other aids to boost their academic performance and mitigate student attrition [ 10 , 13 ].
Hace 2 días · In our cohort of 1210 patients, 28.4% (344) faced readmission or mortality within 90 days post-discharge. Our study pinpointed 10 significant indicators—spanning peripheral immune cells and traditional clinical metrics—that predict these outcomes, with the support vector machine (SVM) model showing superior performance.
Hace 2 días · I'm currently working on a balanced multiclass classification problem (not multilabel, but multicategory) and trying to determine the most suitable metrics for evaluating model performance. I understand the importance of accuracy but I'm contemplating whether to complement it with macro or weighted average F1 scores.
Hace 5 días · As ML engineers, we define performance measures such as accuracy, F1 score, Recall, etc., which compare the predictions of a machine learning model with the known values of the dependent variable in a dataset. GET A DEMO. Why ML Model Monitoring is Critical to Improve Performance?
Hace 5 días · Machine Learning. Advanced decoding models including time generalization. Encoding Models. Receptive field estimation with optional smoothness priors. Statistics. Parametric and non-parametric, permutation tests and clustering. Connectivity.
