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- Continuous attributes are discretized through maximum entropy method. 连续属性通过极大熵方法离散化。
- For example, in a decision tree mining model the viewer will use Cyan to display continuous attributes. 例如,在树挖掘模型中,查看器将使用青色来显示连续属性。
- This paper proposes a new discretization algorithm for continuous attributes to incomplete information systems. 针对不完备信息系统提出了一种新的粗糙集离散化算法。
- Continuous attributes are displayed with a diamond chart, which represents the mean and standard deviation in each cluster. 连续属性以菱形图显示,表示每个分类中的平均偏差和标准偏差。
- By use of the super-club data and entropy of the information table, the discretization of continuous attributes was implemented. 根据条件属性与决策属性之间的依赖关系及相对信息熵概念，实现了连续属性的离散化。
- Third, This paper puts forward a new discretization method for the continuous attributes, which is based on the clustering and rough sets theory. 最后，本文基于聚类方法、结合粗集理论提出了一种新的连续属性离散化方法。
- Discretization of continuous attributes is always one of the key problems that need urgent solutions in rough sets theory. 连续属性的离散化是粗糙集理论亟待解决的关键问题之一。
- But for an original database with large continuous attributes values, how to discretize data reasonably is a noticeable problem. 对于一个包含大量连续属性值的原始数据库，如何根据需要合理对数据进行归一化处理应该是粗糙集理论中值得注意的一个问题。
- This algorithm method can classify the data objects dynamically and realize the discretizaion of taxpayers’ continuous attributes. 该算法能够动态地对数据对象进行类别划分，实现纳税人连续型属性的离散化。
- The Microsoft Decision Trees algorithm is a classification and regression algorithm for use in predictive modeling of both discrete and continuous attributes. Microsoft决策树算法是一种分类和回归算法,用于离散属性和连续属性的预测性建模。
- Discrete attributes are shown as colored bars, and continuous attributes are shown as a diamond chart that represents the mean and standard deviation in each cluster. 离散属性显示为彩条,连续属性显示为菱形图,表示每个分类中的平均偏差和标准偏差。
- In this article,the authors propose a new method for discretization of continuous attributes based on FCM cluster using feedback information from decision table consistency. 讨论模糊C均值聚类算法在决策表条件属性对决策属性的相容程度的指导下对粗集理论中的连续属性进行离散化的一种新算法。
- The paper put forward a method of discretization of continuous attributes based on discernibility matrix and revised the discrete result by average mutual information. 本文基于可辨识矩阵提出一种连续属性离散化的方法，并利用平均互信息量对离散化结果进行修正。
- In this article, the authors propose a new method for discretization of continuous attributes based on FCM cluster using feedback information from decision table consistency. 摘要讨论模糊C均值聚类算法在决策表条件属性对决策属性的相容程度的指导下对粗集理论中的连续属性进行离散化的一种新算法。
- First, fuzzy C-means (FCM) clustering method based on a new cluster validity index is used to obtain the optimal discrete values of the continuous attributes. 采用基于一种新的聚类有效性准则函数的模糊C均值聚类算法对连续属性进行离散化；
- Because traditional rough set theory can only deal with the discrete attributes in database.So,the discretization of continuous attributes is one of the main problems in rough sets. 由于粗糙集只能对离散属性进行处理,因而连续属性的离散化也就成了粗糙集的主要问题之一。
- Finally an illustrated example shows that the way has preferable practicality and availability, can commendably apply to data mining project which contains plentiful continuous attributes. 最后通过具体案例表明了该方法具有较好的实用性、有效性，可以很好地应用在含有大量连续属性的数据挖掘项目中。
- Theoretical Ap proach and Its Application of Continuity Attribute Analysis. 连续性属性分析理论探讨及应用。
- A rule learning algorithm on continuous attributes space 连续属性空间上的规则学习算法
- Having the qualities or attributes of a wizard. 魔法的，术士的有巫师的特点或性质的
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