Classification of Real Imbalanced Cardiovascular Data Using Feature Selection and Sampling Methods: A Case Study with Neural Networks and Logistic Regression.
Jale BektasTurgay IbrikciI. Türkay ÖzcanPublished in: Int. J. Artif. Intell. Tools (2017)
Keyphrases
- logistic regression
- feature selection
- support vector
- sampling methods
- class imbalance
- neural network
- decision trees
- imbalanced data
- pattern recognition
- data analysis
- logistic regression models
- data sets
- data distribution
- classification accuracy
- data points
- feature set
- training samples
- feature space
- imbalanced datasets
- high dimensional data
- training data
- classification models
- data mining
- prior knowledge
- machine learning
- feature extraction
- classification trees
- training dataset
- class distribution
- raw data
- pairwise
- unsupervised learning
- least squares
- knowledge discovery
- learning process
- active learning