Daqing Wang

with 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 Daqing Wang trusts

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

1. Ron Kohavi (in Statistical Learning Theory)
2. Eric Bauer (in Statistical Learning Theory)
3. Ross S. Lunetta (in Atmospheric Science)
4. Yang Shao (in Atmospheric Science)

Papers from Daqing Wang's perspective

Ordered by how strongly the researchers Daqing Wang 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