Feifan Deng

2016

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Whom Feifan Deng trusts overall

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

1. Eric Bauer
2. Yang Shao

Papers from Feifan Deng's perspective

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

1. An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants
2. Comparison of support vector machine, neural network, and CART algorithms for the land-cover classification using limited training data points
3. Approximate Statistical Tests for Comparing Supervised Classification Learning Algorithms
4. Very Simple Classification Rules Perform Well on Most Commonly Used Datasets
5. Bagging Predictors
6. On Bias, Variance, 0/1—Loss, and the Curse-of-Dimensionality
7. Multi-Interval Discretization of Continuous-Valued Attributes for Classification Learning
8. Boosting the margin: A new explanation for the effectiveness of voting methods
9. Experiments with a New Boosting Algorithm
10. C4.5: Programs for Machine Learning

Their papers

• Assessment of Groundwater Potential Based on Multicriteria Decision Making Model and Decision Tree Algorithms (2016) — 105 citations