Automated Machine Learning Pipeline Framework for Classification of Pediatric Functional Nausea Using High-Resolution Electrogastrogram.
Joseph D. OlsonSuseela SomarajanNicole D. MuszynskiAndrew H. ComstockKyra E. HendricksonLauren ScottAlexandra RussellSari A. AcraLynn WalkerLeonard A. BradshawPublished in: IEEE Trans. Biomed. Eng. (2022)
Keyphrases
- machine learning
- high resolution
- pattern recognition
- classification accuracy
- decision trees
- support vector
- supervised learning
- support vector machine
- machine learning methods
- text classification
- statistical learning
- supervised machine learning
- data sets
- automated classification
- support vector machine svm
- data preparation
- training samples
- low resolution
- feature space
- preprocessing
- feature selection
- unsupervised learning
- knowledge acquisition
- active learning
- remote sensing
- high frequency
- multispectral
- classification method
- feature vectors
- learning tasks
- pattern classification
- automatic classification
- classification scheme
- artificial intelligence