Roweida Mohammed

Artificial Intelligence · 2020

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

Subfields

Whom Roweida Mohammed trusts overall

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

  1. Andrew P. Bradley
  2. Yoav Freund
  3. Hui Han
  4. Guillaume Lemaitre
  5. Robert E. Schapire
  6. Nitesh V. Chawla
  7. C. J. Rijsbergen
  8. Fabian Pedregosa
  9. Wenyuan Wang
  10. Fernando Nogueira

Who trusts Roweida Mohammed overall

  1. Hussain Alibrahim
  2. Simone A. Ludwig

Papers from Roweida Mohammed's perspective

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

  1. SMOTE: Synthetic Minority Over-sampling Technique
  2. The use of the area under the ROC curve in the evaluation of machine learning algorithms
  3. A decision-theoretic generalization of on-line learning and an application to boosting
  4. Scikit-learn: Machine Learning in Python
  5. Borderline-SMOTE: A New Over-Sampling Method in Imbalanced Data Sets Learning
  6. Learning From Imbalanced Data
  7. Imbalanced-learn: A Python Toolbox to Tackle the Curse of Imbalanced Datasets in Machine Learning
  8. Matplotlib: A 2D Graphics Environment
  9. SPECIAL ISSUE ON LEARNING FROM IMBALANCED DATA SETS
  10. Effective detection of sophisticated online banking fraud on extremely imbalanced data (World wide web (Bussum))

Their papers