Sattar Hashemi

Artificial Intelligence · 2016

A researcher in the Science corpus: 1 paper; trusts 11 researchers and is trusted by 17 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 16 citations into it; #11,650 of 35,345 by trust here, #27,551 by citations
• Accounting — 6 citations into it
• Information Systems — 5 citations into it

Whom Sattar Hashemi trusts overall

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

1. Jaka Demsar
2. S. Kotsiantis
3. Trevor J. Hastie
4. Gary M. Weiss
5. Ryan M. Rifkin
6. Alberto Fernández
7. Gustavo E. A. P. A. Batista
8. Nitesh V. Chawla
9. Ronaldo Cristiano Prati
10. Jesús Alcalá-Fdez

Who trusts Sattar Hashemi overall

1. Alberto Fernández
2. Mikel Canizo
3. Amin Sharififar
4. Min-Ling Zhang

Papers from Sattar Hashemi's perspective

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

1. The use of the area under the ROC curve in the evaluation of machine learning algorithms
2. Bagging Predictors
3. A study of the behavior of several methods for balancing machine learning training data
4. SMOTEBoost: Improving Prediction of the Minority Class in Boosting
5. Statistical Comparisons of Classifiers over Multiple Data Sets
6. Experiments with a New Boosting Algorithm
7. Borderline-SMOTE: A New Over-Sampling Method in Imbalanced Data Sets Learning
8. Evaluating boosting algorithms to classify rare classes: comparison and improvements (Proceedings 2001 IEEE International Conference on Data Mining)
9. Class Imbalances versus Class Overlapping: An Analysis of a Learning System Behavior
10. Classification by Pairwise Coupling

Their papers

• To Combat Multi-Class Imbalanced Problems by Means of Over-Sampling Techniques (2016) — 363 citations