T. Vafeiadis

Statistical Learning Theory · 2015

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Statistical Learning Theory — 5 citations into it

Whom T. Vafeiadis trusts overall

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

1. Nitesh V. Chawla
2. Max Kuhn
3. Chih-Ping Wei
4. Robert E. Schapire
5. I-Tang Chiu
6. Kjell Johnson
7. Tom Fawcett
8. Wai-Ho Au

Papers from T. Vafeiadis's perspective

Ordered by how strongly the researchers T. Vafeiadis 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. A training algorithm for optimal margin classifiers
3. An introduction to ROC analysis
4. A Brief Introduction to Boosting
5. Predicting subscriber dissatisfaction and improving retention in the wireless telecommunications industry (IEEE Trans. Neural Networks Learn. Syst.)
6. Boosting: Foundations and Algorithms
7. Bagging and Boosting Classification Trees to Predict Churn
8. A novel evolutionary data mining algorithm with applications to churn prediction (IEEE Transactions on Evolutionary Computation)
9. Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management
10. Turning telecommunications call details to churn prediction: a data mining approach (Expert systems with applications)

Their papers

• A comparison of machine learning techniques for customer churn prediction (2015) — 420 citations