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31. To research on market segmentation and decision tree of knowledge, the papers realize the basic algorithm.

32. "It's more of a Christmas tree approach where you constantly have to go back to the top to work yourself through the maze of the decision tree," Castonguay said.

33. This D-S decision tree is a new classification method applied to uncertain data and shows good performance and can efficiently avoid combinatorial explosion.

34. This article focuses on the pruning strategy of the decision tree pruning.

35. The principle and the decision steps of decision tree analysis method are introduced; at the same time the application of this method in construction bidding is illustrated. Sentencedict.com

36. But most of the existent decision tree algorithms suffer a problem, namely multivalue bios, in the process of attribute selection.

37. The results shows that the Bayesian Belief Network has better performance than the Decision Tree and Support Vector Machine.

38. In this paper, we have analyzed the characteristics of Chinese foreign exchange money laundering activities, and combined the decision tree approach with financial domain knowledge.

39. But, fuzzy decision tree induction is an important way for learning from examples with fuzzy representation.

40. Two methods for text categorization fuzzy rule extraction are presented based on fuzzy decision tree.

41. Experiment is the traditional method for analysing multivalue bios of decision tree algorithm, but it has a fault that we must have the expertise of the specific field.

42. Scalar Product Protocol is the keystone in building privacy-preserving decision tree.

43. The decision tree constructed with the new standard of attribute selection has the following characteristics:fewer leaf nodes, fewer levels of average depth, better generalization of leaf nodes.

44. Multivalue bios may result in inducing wrong knowledge from data set, and consequently result in the decline of the performance of decision tree.

45. Decision tree is a basic learning method in machine learning and data mining.

46. An MSS spectral form correlation model and a histogram decision tree classifier are presented.

47. This inference machine is based on decision tree, because of rules saving characteristic.

48. The comparable and analyzable experiment shows that this algorithm can make a minimize decision tree whose rules are true.

49. As a perfect quantitative analysis method the decision tree analysis method is practicable and simple and realize scientific decision in bid invitation.

50. In this paper, we implement an improved method based on decision tree on a specific problem of simulated local-area network on which a network intrusion detector is built.

51. The calculation of the decision tree uses the C4.5 algorithm, which takes information gain ratio as attribute choice criterion.

52. A decision tree is a graphic model of a decision process.

53. Comparing with the decision tree built by the existing algorithm, the decision tree built by the refined algorithm has a lower weighted path length(WPL), and more closer to optimal decision tree.

54. The data based on the decision tree inductive classification are applied to the analysis of the power plant heat cost, combined with the characteristics of electric power industry.

55. Methods:The decision tree classifier is used as a tool and the rate of classification accuracy is used to measure the consistency.

56. C 4.5 decision tree classifier, using the C language. U.S. with reference.

57. Second, this paper proposes a new decision tree algorithm, AF algorithm, which avoids multivalue bios.

58. Finally by comparison with C4.5 system, it is further confirmed that gradual increasing of the parameter within this interval may have the same effect as the crisp decision tree pruning.

59. The second method uses Bayes classifier in the first step and decision tree classifier in the second step.

60. Therefore, the decision tree method is a simple and useful tool for computer-aided diagnosis.