Jun Ryeol Park
Artificial Intelligence · 2018
A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 8 citations into it
Whom Jun Ryeol Park trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Papers from Jun Ryeol Park's perspective
Ordered by how strongly the researchers Jun Ryeol Park trusts endorse each paper. Same corpus, a different order for every researcher.
- SMOTE: Synthetic Minority Over-sampling Technique
- A study of the behavior of several methods for balancing machine learning training data
- Borderline-SMOTE: A New Over-Sampling Method in Imbalanced Data Sets Learning
- ADASYN: Adaptive synthetic sampling approach for imbalanced learning (IEEE World Congress on Computational Intelligence)
- Improving Identification of Difficult Small Classes by Balancing Class Distribution (Conference on Artificial Intelligence in Medicine in Europe)
- An introduction to ROC analysis
- Imbalanced-learn: A Python Toolbox to Tackle the Curse of Imbalanced Datasets in Machine Learning
- Machine learning models and bankruptcy prediction (Expert systems with applications)
- MetaCost: a general method for making classifiers cost-sensitive
- The use of the area under the ROC curve in the evaluation of machine learning algorithms