HFS-LightGBM: A machine learning model based on hybrid feature selection for classifying ICU patient readmissions.
Yan QiuShuai DingNingguang YaoDongxiao GuXiaojian LiPublished in: Expert Syst. J. Knowl. Eng. (2021)
Keyphrases
- feature selection
- machine learning
- clinical data
- intensive care unit
- text classification
- intensive care units
- text categorization
- feature engineering
- model selection
- mutual information
- heart rate
- support vector
- medical data
- patient data
- support vector machine
- classification accuracy
- active learning
- feature space
- multi class
- reinforcement learning
- dimensionality reduction
- feature selection algorithms
- electronic health records
- automatic classification
- medical experts
- machine learning methods
- learning algorithm
- statistical analysis
- pattern recognition
- knowledge discovery
- supervised learning
- natural language processing
- machine learning algorithms
- knowledge acquisition
- feature ranking
- data analysis
- feature set
- classification models
- inductive learning
- feature subset
- microarray data
- unsupervised learning
- feature generation
- blood pressure
- data preparation
- medical knowledge
- data sets
- medical records
- clinical practice
- high risk
- knowledge base
- learning models
- learning tasks
- monitoring system
- decision trees
- text mining