"Missing Is Useful': Missing Values in Cost-Sensitive Decision Trees.
Shichao ZhangZhenxing QinCharles X. LingShengli ShengPublished in: IEEE Trans. Knowl. Data Eng. (2005)
Keyphrases
- missing values
- cost sensitive learning
- cost sensitive
- decision trees
- naive bayes
- decision tree algorithm
- missing data
- incomplete data
- misclassification costs
- missing information
- missing attribute values
- multi class
- base classifiers
- class distribution
- active learning
- machine learning algorithms
- decision rules
- training set
- fraud detection
- logistic regression
- training data
- class imbalance
- high dimensional data
- ensemble methods
- nearest neighbour
- probability estimation
- error rate
- classification algorithm
- machine learning
- imputation methods
- data mining