Ebrahim Omidvar
Global and Planetary Change · 2019–2020
A researcher in the Science corpus: 2 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Global and Planetary Change — 42 citations into it
- Management, Monitoring, Policy and Law — 27 citations into it
- Mechanical Engineering — 8 citations into it
Whom Ebrahim Omidvar trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Papers from Ebrahim Omidvar's perspective
Ordered by how strongly the researchers Ebrahim Omidvar trusts endorse each paper. Same corpus, a different order for every researcher.
- Estimating Attributes: Analysis and Extensions of RELIEF
- Landslide susceptibility modelling using GIS-based machine learning techniques for Chongren County, Jiangxi Province, China. (Science of the Total Environment)
- Spatial prediction models for shallow landslide hazards: a comparative assessment of the efficacy of support vector machines, artificial neural networks, kernel logistic regression, and logistic… (Landslides)
- The meaning and use of the area under a receiver operating characteristic (ROC) curve.
- A decision-theoretic generalization of on-line learning and an application to boosting
- Landslide susceptibility mapping using J48 Decision Tree with AdaBoost, Bagging and Rotation Forest ensembles in the Guangchang area (China)
- The Nature of Statistical Learning Theory
- Feature Selection for Classification
- GIS-based landslide susceptibility evaluation using a novel hybrid integration approach of bivariate statistical based random forest method
- A Review and Empirical Evaluation of Feature Weighting Methods for a Class of Lazy Learning Algorithms
Their papers
- Flood Detection and Susceptibility Mapping Using Sentinel-1 Remote Sensing Data and a Machine Learning Approach: Hybrid Intelligence of Bagging Ensemble Based on K-Nearest Neighbor Classifier (2020) — 334 citations
- New Ensemble Models for Shallow Landslide Susceptibility Modeling in a Semi-Arid Watershed (2019) — 114 citations