Decision Trees Accuracy Improvement for Production Errors Classification.
Michal KebísekLukás SpendlaPavol TanuskaLukas HrckaPublished in: CSOS (1) (2018)
Keyphrases
- decision trees
- classification accuracy
- predictive accuracy
- machine learning algorithms
- accuracy rate
- information gain
- machine learning
- induction algorithms
- associative classifiers
- decision rules
- training set
- naive bayes
- error analysis
- classification models
- high accuracy
- classification rules
- decision tree learners
- feature construction
- rule sets
- training data
- classification method
- roc analysis
- pattern classification
- fold cross validation
- error rate
- support vector machine svm
- feature vectors
- pattern recognition
- feature selection
- error reduction
- classification algorithm
- decision tree learning
- random forest
- text classification
- attribute selection
- classification rate
- decision tree induction
- high predictive accuracy
- decision tree learning algorithm
- data mining
- rule induction
- generalization ability
- machine learning methods
- benchmark datasets
- training samples
- feature set
- multi class
- computational cost
- support vector