Biomedical engineering Application of Machine Learning and Functional Data Analysis in Classification and Clustering of Functional Near Infrared Spectroscopy Signal in Response to Noxious Stimuli DREXEL UNIVERS
, learning types (suppressed (classification, regression), non-suppressed (clustering, association)), year of publication and ML methods used. We discuss a sustainable, resilient and inclusive urban form by including environmental, socio-economic elements and indicators in addition to classical ...
Machine learning (ML) is a subset of Artificial Intelligence (AI) that involves the development of algorithms and statistical models enabling computers to perform tasks without explicit instructions. By utilizing patterns and inference derived from data, ML algorithms can improve their performance over t...
transformation (FFT), Fuzzy logic, and Park's vector analysis. The latest development in artificial intelligence (AI) is 'transfer learning', which can detect failure patterns of different devices. This technique can be used instead of MCSA to find localized anomalies and has been suggested in p...
Quick and accurate medical diagnoses are crucial for the successful treatment of diseases. Using machine learning algorithms and based on laboratory blood test results, we have built two models to predict a haematologic disease. One predictive model used
Therefore, we believe that a new theory and methodology based on clustering techniques, in combination with proxy models, must be developed to reduce computational costs and reliably solve real-world sequential decision-making problems. Author contributions Amine wrote the paper and contributed to ...
Clustering has primarily been used as an analytical technique to group unlabeled data for extracting meaningful information. The fact that no clustering al
Finally, the application Clustering is rarely the main object of the studies but plays a minor role in the Consumption sector. However, clustering is often conducted as a pre-processing step within the studies. Moving on to the analysis of the approach category, Fig. 6 shows a shift in the...
An extreme value prediction method based on clustering algorithm. Reliability Engineering and System Safety, 2022, 222: 108442. DOI:10.1016/j.ress.2022.108442 114. Zhang, W., He, Y., Li, P. et al. Graph regression for pressure peak prediction in fracturing processes. Journal of Petroleum ...
Finite mixture models are frequently used for clustering, because the clustering task can be viewed as determining which of the K components each data point came from. Indeed, the popular K-means algorithm taught in "Machine Learning 101" can be viewed as fitting a finite mixture model under ...