Caleb Robinson

2017

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

Whom Caleb Robinson trusts overall

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

1. Ron Kohavi
2. Jerome H. Friedman
3. Fabian Pedregosa

Who trusts Caleb Robinson overall

1. Ying Sun
2. Aowabin Rahman
3. F. Haghighat

Papers from Caleb Robinson's perspective

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

1. Greedy function approximation: A gradient boosting machine.
2. Scikit-learn: Machine Learning in Python
3. A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection
4. Opportunities and insights for reducing fossil fuel consumption by households and organizations (Nature Energy)
5. Development of prediction models for next-day building energy consumption and peak power demand using data mining techniques
6. Bagging Predictors
7. Information Theory: 1948-1998 - Guest Editorial
8. Experiments with a New Boosting Algorithm
9. On Bias, Variance, 0/1—Loss, and the Curse-of-Dimensionality
10. Multi-Interval Discretization of Continuous-Valued Attributes for Classification Learning

Their papers

• Machine learning approaches for estimating commercial building energy consumption (2017)