Keywords
Affiliated Institutions
Related Publications
CLOUDS: a decision tree classifier for large datasets
Classification for very large datasets has many practical applications in data mining. Techniques such as discretization and dataset sampling can be used to scale up decision tr...
Bagging, boosting, and C4.S
Breiman's bagging and Freund and Schapire's boosting are recent methods for improving the predictive power of classifier learning systems. Both form a set of classifiers that ar...
The random subspace method for constructing decision forests
Much of previous attention on decision trees focuses on the splitting criteria and optimization of tree sizes. The dilemma between overfitting and achieving maximum accuracy is ...
Approximate Splitting for Ensembles of Trees using Histograms
Recent work in classification indicates that significant improvements in accuracy can be obtained by growing an ensemble of classifiers and having them vote for the most popular...
Binarized Support Vector Machines
The widely used support vector machine (SVM) method has shown to yield very good results in supervised classification problems. Other methods such as classification trees have b...
Publication Info
- Year
- 1992
- Type
- article
- Volume
- 13
- Issue
- 2
- Pages
- 83-87
- Citations
- 20
- Access
- Closed
External Links
Social Impact
Social media, news, blog, policy document mentions
Citation Metrics
Cite This
Identifiers
- DOI
- 10.1016/0167-8655(92)90037-z