Michelle Sapitang

Artificial Intelligence · 2020

A researcher in the Science corpus: 2 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 5 citations into it

Whom Michelle Sapitang trusts overall

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

1. Ron Kohavi
2. Miroslav Kubat
3. Rob J Hyndman
4. Roohollah Noori
5. Anne B. Koehler
6. Josef Kittler

Papers from Michelle Sapitang's perspective

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

1. Pattern recognition : a statistical approach
2. Another look at measures of forecast accuracy
3. A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection
4. An Introduction to Machine Learning
5. Machine Learning: An Applied Econometric Approach
6. Uncertainty analysis of developed ANN and ANFIS models in prediction of carbon monoxide daily concentration
7. Experiments with a New Boosting Algorithm
8. Bagging Predictors
9. Boosting the margin: A new explanation for the effectiveness of voting methods
10. The Strength of Weak Learnability

Their papers

• Enhancement of Groundwater-Level Prediction Using an Integrated Machine Learning Model Optimized by Whale Algorithm (2020) — 96 citations
• Machine Learning Application in Reservoir Water Level Forecasting for Sustainable Hydropower Generation Strategy (2020) — 99 citations