Evolving data sets to highlight the performance differences between machine learning classifiers.
Thomas RawayJ. David SchafferKenneth J. KurtzHiroki SayamaPublished in: GECCO (Companion) (2012)
Keyphrases
- machine learning
- data sets
- machine learning algorithms
- machine learning methods
- decision trees
- training data
- training set
- benchmark data sets
- machine learning approaches
- supervised classification
- feature selection
- induction algorithms
- meta learning
- computer science
- inductive learning
- statistically significant
- learning algorithm
- pattern recognition
- multiple classifier systems
- support vector
- roc analysis
- learning classifier systems
- linear classifiers
- multiple classifiers
- support vector machine
- naive bayes
- classification systems
- classification trees
- feature set
- unseen data
- feature selection algorithms
- ensemble classifier
- incomplete data sets
- classifier combination
- roc curve
- classification models
- training examples
- data mining
- active learning
- information extraction
- supervised learning
- text classification
- test set
- statistical methods
- learning tasks
- learning problems
- svm classifier
- classification algorithm
- microarray data
- training samples
- knowledge acquisition
- classification method
- text mining
- artificial intelligence
- ensemble learning