Conditional entropy

Rules extraction method of decision tree based on new conditional entropy

基于新的条件熵的决策树规则提取方法

A method of discretization of continuous attributes in rough sets based on conditional entropy

一种基于条件熵的粗糙集连续属性离散化方法

A new conditional entropy and knowledge reduction algorithms are proposed .

提出新的条件信息熵及其高效知识约简算法。

Conditional Entropy and Mutual Information in Random Cascading Processes

自相似随机级联过程中的条件熵和信息量

By applying conditional entropy , a new algorithm for deciding sliding window size is proposed .

采用条件熵的判定方法，提出了一种确定滑动窗口大小的算法。

Estimation of lossless image compression bounds based on multi-scale conditional entropy and memory measurement

利用多尺度条件熵和记忆性度量估计图像无损压缩极限

And weighted infromation entropy and weighted conditional entropy of information system based on set-value function is presented also .

还提出了基于一般的集值函数的信息系统加权信息熵和条件熵概念。

A class of limit theorems for the relative entropy density and the random conditional entropy of finite Markov chains

关于有限马氏链相对熵密度和随机条件熵的一类极限定理

The Random Conditional Entropy of Finite Non-homogeneous Markov Chains and an Extension of the Shannon Theorem

有限非齐次马氏链的随和条件熵与Shannon定理的一个推广

Regarding this aspect , this paper builds a measure criterion on the variable precision conditional entropy of the scoped boundary .

针对这个问题，本文构建了一种基于边界域的变精度条件熵的度量标准。

Its feasibility was proved by calculation conditional entropy of 2-step and k-order Markov predictor .

通过分别对二步和k阶Markov预测器条件熵的计算，在理论上了证明了二步Markov预测器的可行性。

As an application , we calculate the conditional entropy of rossler-rossler and rossler-lorenz systems .

然后分别计算Rossler-Lorenz与Rossler-Rossler混沌系统双向耦合的条件熵。

The basic idea is that we use entropy and conditional entropy to measure whether a feature type grasps some of the information for syntactic structure prediction .

其基本思想是利用信息论中熵与条件熵的度量来显示一个特征类型是否抓住了预测句法结构的主要信息。

Secondly , the rule order in the classification rule set is arranged by using conditional entropy as a measurement factor so that the classification efficiency is enhanced .

其次，采用条件信息熵作为分类规则的度量因子，对分类规则进行排序，从而进一步提高了分类规则的分类效率；

Shannon 's information theory was also applied to the SPECT imaging field . The physics was evaluated to analyze the conditional entropy and the mutual information .

将Shannon信息论应用到SPECT成像领域，根据在SPECT系统中信息量、条件熵、互信息熵的意义，提出了评估投影数据完备性的原理和方法。

Lossless compression bounds of images naturally acquired by various imaging sensors are estimated using a practical method based on multi scale conditional entropy and memory measurement .

为估计利用各类成像传感器自然获取图像的无损压缩极限，提出一个利用多尺度条件熵和记忆性度量的实用方法。

The conditional entropy is the basis to determine the contribution of a single model for the forecast result . Fuzzy comprehensive evaluation is used to determine the corresponding model weights .

将条件熵作为判断单一模型对结果贡献的依据，运用模糊综合评判确定对应的模型权重。

After that , three new algorithms for key frame extraction are presented , which are based on clustering algorithm with adaptive threshold , based on covariance and based on conditional entropy .

接着，详细介绍了本文提出的三种新的关键帧提取技术，分别为：基于自适应阈值聚类的方法、基于协方差的方法以及基于条件熵的方法。

The attribute weight and weighted support of default regular are defined by using the conditional entropy and a mining algorithm of default regulars are given for inconsistent database .

针对不一致数据库，定义属性权重及缺省规则加权支持度概念，在此基础上给出一种缺省规则挖掘算法。

In this paper , I propose a method to compute the conditional entropy for each sub dataset , and discuss in detail the validity and correctness of the algorithm .

给出了使用条件熵计算各个子分类器权值的方法。详细论述了算法的有效性和正确性。

The results show that the negative quantum conditional entropy can be regarded as a entanglement measure of an arbitrary states of the two identical two-level atoms with simple calculated analytically .

结果表明，负值条件熵能够作为该条件下两全同二能级原子同时与单模腔场相互作用任意态的，容易解析计算的纠缠度。

Discuss the generation of test strategy for diagnosis based on information gain maximization and conditional entropy minimization . This approach can be used into the testability analysis and the optimization of test strategy for diagnosis .

研究了基于信息增益最大和基于条件熵最小的诊断测试策略生成问题，该方法可用于系统的可测性分析、诊断测试策略的优化等方面。

At first , an algorithm for calculating the core of a decision table is proposed based on the domain-oriented data-driven data mining theory . Secondly , an algorithm for finding multiple reductions based on conditional entropy is proposed .

首先，基于面向领域的数据驱动的数据挖掘模型思想，提出了一个求核属性的算法和一个基于信息熵的求多个属性约简的算法。

Regular conditional entropy is used to make the statistic reduction , and the modified fuzzy C-mean clustering algorithm to discrete the raw data . Bayes decision under minimum risk is utilized to deal with the contradictory diagnostic rules .

通过改进的模糊C-均值聚类算法对原始故障数据加以量化，采用正则条件熵进行诊断知识系统的统计约简，对不协调的诊断规则利用最小风险Bayes决策理论加以分析处理。

Theoretical analysis states clearly that in case of weighing the consistency of decision system , this measure criterion and the conditional entropy has something in common on recognition , and this measure criterion is also equivalent to the relative regular domain .

理论分析表明在衡量决策系统一致性程度问题时，该度量标准与条件熵具有相同的判别作用，与相对正域等效。

Finally , the experiment results show the correctness and the validity of the algorithm by taking UCI data as the formal context . ( 2 ) A classification rule acquisition algorithm based on the concept lattice and conditional entropy is presented .

采用UCI数据作为形式背景，实验验证了该算法的正确性和有效性。第二、基于概念格和信息熵的分类规则提取算法。

The conditional entropy of two symbolic sequences which are encoded faithfully from two different time series is minimized at the zero relative shift of the two time series if the two time series have their origins in the same underlying dynamics .

通过粗粒化方法得到符号序列，如果两个符号序列的条件熵在相对位移为零时达到最小值，那么这两个时间序列可能属于同一个动力学系统。

According to the conclusion that conditional entropy will be no more than the unconditional entropy , we can see the Context model can effectively reduce the entropy of the source of information , thereby reducing the code length of the image coding .

根据条件熵必不超过无条件熵这一结论，可知Context模型可以有效的减少信源的信息熵，从而减少图像编码的码长。

This algorithm concepts the importance of the cut point based on the conditional entropy of the scoped boundary , eliminate cut point with zero importance , so as to improve the running efficiency of the decision making system , reduce the scales of the decision table .

该算法定义了基于边界域条件熵的断点重要性，删除重要性为零的断点，从而降低决策表的规模，提高面向决策系统算法的运行效率。

An Efficient Knowledge Reduction Algorithm Based on New Conditional Information Entropy

一种基于新的条件信息熵的高效知识约简算法