Interpretation of Data Mining Prediction Model Using Decision Tree

  • Published : 2000.12.01


Data mining usually deal with undesigned massive data containing many variables for which their characteristics and association rules are unknown, therefore it is actually not easy to interpret the results of analysis. In this paper, it is shown that decision tree can be very useful in interpreting data mining prediction model using two real examples.


  1. AnswerTree를 이용한 데이터마이닝 의사결정나무분석 최종후;한상태;강현철;김은석
  2. Data Mining Techniques for Marketing, Sales, and Customer Support Berry, M.J.A.;Linoff, G.
  3. Classification and regression trees Breiman, L.;J.H. Friedman;R.A. Olshen;C.J. Stone
  4. Applied Multivariate Statistical Analysis Johnson, R.A.;Wichern, D.W.
  5. Applied Statistics v.29 An exploratory technique for investigating large quantities of categorical data Kass, G.
  6. Self-Organizing Maps Kohonen, T.
  7. Statistica Sinica v.7 Split selection methods for classification trees Loh, W.;Shih, Y.
  8. C4.5 Programs for machine learning Quinlan, J.R.
  9. Neural Networks for Statistical Modeling Smith, M.