| 1. | Decision tree classification algorithm based on bayesian method
基于贝叶斯方法的决策树分类算法 |
| 2. | This paper is a study on decision tree classification algorithms , which mainly includes two parts
本文主要对决策树分类算法展开研究，主要包含两个内容： 1 |
| 3. | In the first part , two decision tree classification algorithms , sliq and sprint , is studied , because they are the most useful at present
研究了sliq算法和sprint算法。因为这两个算法可以说是目前决策树算法中最有效的。 |
| 4. | Secondly , decision tree classification model and logistic regression model are performed to rock mass quality assessment , based on sas / enterprise miner
应用sas enterpriseminer系统的决策树分类算法和logistic回归算法进行岩体的质量分级评价。 |
| 5. | A further study has been made about decision tree classification , bayesian network , and discretization of conntinuous attributes , at the same time many kinds of classfication algorithms have been achieved
对决策树分类、贝叶斯网络和连续属性的离散化问题进行了的研究，实现了多种分类算法。 |
| 6. | When we design the classification , we combine the tree classification and the support vector machines in order to improve the ability of combining experiences and performance of generalization
在模式识别的分类器设计上，我们采用了树分类器和支持向量机相结合的方法，提高了分类器经验结合的能力和泛化能力。 |
| 7. | We also make plenty of classification experiments with data sets from various of different fields , and then analyse and compare the classification capacity of several decision tree classification algorithms and the adaptability to different datas
在来自不同领域的数据集上进行了大量的分类实验，分析和比较了多种决策树分类算法的分类性能和对不同数据的适应性。 |
| 8. | The algorithm of sf _ dt , which bases on the idea of decision tree classification algorithm ids , use the means of file splitting take the place of the means which bases on memory . it improves the scalability of classification algorithm and can deal with very large database
Sf _ dt算法以决策树分类算法id3的基本思想为基础，用基于文件分割的方法代替原有的基于内存的算法，提高了算法的可规模性，可以处理超大规模的数据。 |
| 9. | In the data mining prototype system , apriori algorithm of association rules mining , id3 algorithm of decision tree classification , c4 . 5 pessimism estimate algorithm of decision tree classification and c4 . 5 reduced - error pruning algorithm of decision tree classification are realized
在数据挖掘原型系统中，实现了关联分析的apriori算法、分类的id3决策树算法、 c4 . 5的悲观估计决策树算法和c4 . 5决策树的消除误差修剪算法( reduced - errorpruning ) 。 |
| 10. | Tt _ dtc realizes a series of processes including data preprocess , decision tree classification , producing rules and prediction analysis , which based on the data of train tickets and aimed at the characters of tram tickets which have large amount of data and complex attributes
Tt _ dtc方法以铁路客票数据为基础，以铁路客票营销分析为目的，针对铁路客票信息数据量大、属性复杂、域值广等特点，实现了从数据预处理、决策树生成到规则提取、知识产生等一系列过程。 |
