Tzu-Tsung Wong
Impact in
- Artificial Intelligence top 2%
- Imbalanced Data Classification Techniques
- Bayesian Methods and Mixture Models
- Machine Learning and Data Classification
- Anomaly Detection Techniques and Applications
- Health Informatics top 10%
Papers in
-
- Bayesian Methods and Mixture Models 9
- Bayesian Modeling and Causal Inference 5
- Imbalanced Data Classification Techniques 4
- Machine Learning and Data Classification 4
- Text and Document Classification Technologies 4
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- Statistical Methods and Inference 4
- Advanced Statistical Methods and Models 3
- Co-authors
- Chun‐Nan Hsu (2 shared papers)Ching‐Han Hsu (1 shared paper)Kuan-Liang Liu (2 shared papers)
- Journals
- Pattern Recognition (5 papers)IEEE Transactions on Knowledge and Data Engineering (3 papers)Data Mining and Knowledge Discovery (2 papers)Expert Systems with Applications (2 papers)Applied Mathematics and Computation (1 paper)
- Partner nations
- TaiwanUnited States
In The Last Decade
Tzu-Tsung Wong
19 papers receiving 2.3k citations
Tzu-Tsung Wong's Hit Papers
Peers
Comparison fields: 5 of 191
- Artificial Intelligence 583
- Health Informatics 20
- Health Information Management 58
- Environmental Engineering 158
- Analytical Chemistry 92
Countries citing papers authored by Tzu-Tsung Wong
This map shows the geographic impact of Tzu-Tsung Wong's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Tzu-Tsung Wong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tzu-Tsung Wong more than expected).
Fields of papers citing papers by Tzu-Tsung Wong
This network shows the impact of papers produced by Tzu-Tsung Wong. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Tzu-Tsung Wong. The network helps show where Tzu-Tsung Wong may publish in the future.
Co-authors
The 3 scholars most cited alongside Tzu-Tsung Wong, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Performance evaluation of classification algorithms by k-fold and leave-one-out cross validation Hit paper breakdown → | 2015 | 1081 |
| 2 | Reliable Accuracy Estimates from k-Fold Cross Validation Hit paper breakdown → | 2019 | 707 |
| 3 | 2017 | 137 | |
| 4 | 1998 | 98 | |
| 5 | 2016 | 61 | |
| 6 | 2011 | 40 | |
| 7 | 2006 | 36 | |
| 8 | Why Discretization Works for Naive Bayesian Classifiers | 2000 | 34 |
| 9 | 2008 | 30 | |
| 10 | 2003 | 26 | |
| 11 | 2010 | 18 | |
| 12 | 2013 | 13 | |
| 13 | 2009 | 11 | |
| 14 | 2021 | 10 | |
| 15 | 2010 | 10 | |
| 16 | 2016 | 7 | |
| 17 | 2020 | 7 | |
| 18 | 2012 | 6 | |
| 19 | Weighted Random Forests for Evaluating Financial Credit Risk | 2019 | 3 |
About Tzu-Tsung Wong
Tzu-Tsung Wong is a scholar working on Artificial Intelligence, Statistics and Probability, Molecular Biology, Information Systems and Computer Vision and Pattern Recognition, having authored 19 papers that have together received 2.3k indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (9 papers), Bayesian Modeling and Causal Inference (5 papers), Imbalanced Data Classification Techniques (4 papers), Machine Learning and Data Classification (4 papers), Statistical Methods and Inference (4 papers), Text and Document Classification Technologies (4 papers), Advanced Statistical Methods and Models (3 papers) and Gene expression and cancer classification (2 papers). The work is most often cited by research in Artificial Intelligence (583 citations), Health Informatics (20 citations), Health Information Management (58 citations), Environmental Engineering (158 citations) and Analytical Chemistry (92 citations). Tzu-Tsung Wong has collaborated with scholars based in Taiwan and United States. Frequent co-authors include Chun‐Nan Hsu, Ching‐Han Hsu and Kuan-Liang Liu. Their work appears in journals such as Pattern Recognition, IEEE Transactions on Knowledge and Data Engineering, Data Mining and Knowledge Discovery, Expert Systems with Applications and Applied Mathematics and Computation.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.