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1. Figure 5.3 is a decision tree for a hypothetical development project to develop and market a new product.

2. Another example is non-numerical decision tree analysis.

3. Firstly, this paper introduced decision tree algorithm theory.

4. A decision tree classifier is used to deal with the first task, which can find the load pattern preliminarily, and reduces the number of parameters to be adjusted.

5. Decision tree,(sentencedict.com) neural networks and Bayesian networks are the main tools of KDD.

6. The thesis researches an algorithm based on decision tree classifier for packet filtering.

7. Secondly, the paper analyzes the limitation of traditional decision tree method existing in credit risks appraisal, proposed a combined optimization and a multiple analysis decision tree algorithms.

8. Results show that the decision tree classifier can achieve higher classification accuracy.

9. Integrating the decision tree method, the classification of multi - classes was realized.

10. A decision tree was established for selecting the optimal inspection and repair strategy.

11. A method for constructing multiway decision tree based on quantized feature values (such as interval values, discrete values and symbolic values) is proposed.

12. A decision tree for substances in Articles is shown in Figure 1. No further action or obligation exists at this stage, although in the future the ECA may require a full registration.

13. Results The decision tree analysis revealed that the predicted costs of 3 cephalosporinses on the treatment of neonatal septicemia were RMB 2490,2586,2270 yuans respectively.

14. Methods:A decision tree was constructed to evaluate health effects of the program, such as averted sequelae of chlamydial infection.

15. Besides, a decision tree classifier(CART) is used to eliminate the unnecessary variables, and reduces the number of parameters to be adjusted.

16. The rank learning algorithm based on the decision tree is able to process categorical data and select relative features.

17. Evolutionary decision tree method has the advantage of global search.

18. With software program , we Simulate the Decision Tree Algorithm in the market segmentation.

19. A decision tree classifier was applied and a scalar product protocol was added, so that the need of privacy preserving is satisfied as well as the advantage of decision tree is retained.

20. We adopts decision tree based on inductive inference methods in selection of model structure.

21. In this paper, an enhanced ID3 decision tree algorithm called ES- ID3 with self-training - and - learning ability is proposed.

22. Improved CART algorithm of decision tree is put forward to solve at the problem of structure identification of ANFIS.

23. Traditionally, we solve a general Bayesian decision problem by using the decision tree analysis method.

24. The choice of attribute selection metric to split has an important impact on the shape and the depth of the resulting decision tree.

25. To meet the requirements of customer credit analysis, sales data from a certain steel mill are analyzed with the help of decision tree.

26. Decision tree classifier is an important data mining problem. The key issue in constructing the decision tree on data streams is to derive the best criterion of internal nodes.

27. According to the relationship between auto correlation function and its spectral density, a new type of decision tree method based on signal analysis theory is proposed in this paper.

28. The paper briefly introduced the concept of privacy preserving data mining technology and studied the application of decision tree classifier in this particular field.

29. Fourthly . making use of Learning from examples based on information theory, machine learning algorithm and machine learning decision tree is realized.

30. Firstly, rough sets is used to reduce condition attribute and remove redundancy attribute, and then, C4.5 is used to build decision tree, rule knowledge is extracted by decision tree pruning.