Snehalata Dongre

Artificial Intelligence · 2013

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

Whom Snehalata Dongre trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Michael Wasikowski
  2. Xue-wen Chen

Who trusts Snehalata Dongre overall

  1. Harsurinder Kaur
  2. Sara Fotouhi
  3. Matloob Khushi

Papers from Snehalata Dongre's perspective

Ordered by how strongly the researchers Snehalata Dongre trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Combating the Small Sample Class Imbalance Problem Using Feature Selection (IEEE Transactions on Knowledge and Data Engineering)
  2. A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Based Approaches
  3. Mining with rarity: a unifying framework
  4. SMOTE: Synthetic Minority Over-sampling Technique
  5. SMOTEBoost: Improving Prediction of the Minority Class in Boosting
  6. MetaCost: a general method for making classifiers cost-sensitive
  7. Learning When Training Data are Costly: The Effect of Class Distribution on Tree Induction (Journal of Artificial Intelligence Research)
  8. The Foundations of Cost-Sensitive Learning
  9. Feature selection for text categorization on imbalanced data (SKDD)
  10. One-Class SVMs for Document Classification (Journal of machine learning research)

Their papers