Travelled to:1 × Australia
1 × Italy
1 × Slovenia
1 × Turkey
3 × USA
Collaborated with:∅ I.H.Witten Z.Zheng G.I.Webb Z.Fu G.Lu D.Zhang G.Zhou F.T.Liu J.S.C.Tan
Talks about:classifi (2) bayesian (2) learn (2) decis (2) boost (2) naiv (2) lazi (2) cost (2) characteris (1) algorithm (1)
Person: Kai Ming Ting
DBLP: Ting:Kai_Ming
Contributed to:
2010
2010
20022000199919971996Wrote 7 papers:
- ICPR-2010-FuLTZ #classification #learning #music #naive bayes #retrieval
- Learning Naive Bayes Classifiers for Music Classification and Retrieval (ZF, GL, KMT, DZ), pp. 4589–4592.
- KDD-2010-TingZLT #estimation
- Mass estimation and its applications (KMT, GTZ, FTL, JSCT), pp. 989–998.
- ICML-2002-Ting #classification #evaluation #using
- Issues in Classifier Evaluation using Optimal Cost Curves (KMT), pp. 642–649.
- ICML-2000-Ting #algorithm #case study #comparative
- A Comparative Study of Cost-Sensitive Boosting Algorithms (KMT), pp. 983–990.
- ICML-1999-ZhengWT #lazy evaluation #learning #naive bayes
- Lazy Bayesian Rules: A Lazy Semi-Naive Bayesian Learning Technique Competitive to Boosting Decision Trees (ZZ, GIW, KMT), pp. 493–502.
- ICML-1997-TingW #modelling
- Stacking Bagged and Dagged Models (KMT, IHW), pp. 367–375.
- ICML-1996-Ting #predict
- The Characterisation of Predictive Accuracy and Decision Combination (KMT), pp. 498–506.