查询词典 conditional expression

This paper proposes a heuristic algorithm for attribution reduction based on conditional entropy by the comprehension and analysis of data mining algorithm based on rough set theory.

本文在理解和分析基于粗糙集理论的数据挖掘算法基础上针对属性约简提出了一个基于条件熵的启发式算法。

In previous researches, the Maximum Entropy model and Conditional Random Field model have been widely used in the study of Chinese Word Segmentation.

分词是汉语自然语言处理研究中非常重要的一个环节，在早先的研究中，最大熵模型和条件随机场模型已经广泛运用到汉语自动分词的工作中。

Examples are given to illustrate the conditional entropy maybe increased,so Shannon's definition of information is not absolutely correct.

从新的角度指出了香农信息论的局限性，指出了它没有考虑信息的可靠性，完备性等特点，指出条件熵的计算公式问题并且进行了纠正，并且举例证明了条件熵可能增加，进而香农信息定义中的不确定性的减少也不是绝对的。

Then, two new algorithms based on conditional entropy, namely CEBARKCC algorithm and CEBARKNC algorithm, are developed in the thesis.

在上述规律的基础上，论文提出了两个新的基于Rough Set理论的启发式知识约简算法：CEBARKCC算法和CEBARKNC算法。

First, regarding the gray values in images as discrete-valued random variables makes it possible to make a much simpler estimation of conditional entropy.

首先，把图像的灰度值视为离散的随机变量，从而可以采用更为简单的方法估计条件熵。

Decision table reduction based on conditional information entropy.

基于条件信息熵的决策表约简。

The roughness of knowledge embodies the granularity of knowledge in algebra view.Two concepts are defined in information view,which are information entropy of knowledge and conditional information entropy of knowledge.

在代数观点中，知识粗糙性体现了知识的粒度；而在信息观中，定义了知识的信息熵和条件信息熵。

Conditional information entropy was used to compute relevance of attributes and it was used in fitness function to assure reduction has fewer attributes and relevance of attributes.

利用条件墒计算属性问的相关性，并将其引入到适值函数中，可以保证所求约简含有较少的属性而且属性间的相关性较小。

Examples are given to illustrate the conditional entropy maybe increased, so Shannon's definition of information is not absolutely correct.

论文摘要：从新的角度指出了香农信息论和信息定义的局限性，指出了它没有考虑信息的可靠性，完备性等特点，指出条件熵的命名不恰当，香农的"条件熵"应该称为加权平均条件熵，并且举例证明了条件熵可能增加，进而香农信息定义中的不确定性的减少也不是绝对的。

Examples are given to prove the conclusion that conditional entropy never increases is not absolute, thus the representation that information is to decrease uncertainty in the definition of information is not absolutely correct, so Shannon's definition of information is not fit.

从多个角度分析了条件熵的定义和计算公式的问题，对条件熵的计算公式进行了纠正，并且举例证明了熵不增并不是绝对的，进而指出香农信息定义中的不确定性的减少也不是绝对的，从而信息的定义名不副实。

Where second earners are not penalised by taxes or where child care is cheap, they can have both.

在第二工资获得者的税率公平的或者孩童照料是便宜的地方她们可以同时选择。

I even remember his little bungalow that we lived in off Melrose that we'd smoke lots of pot in.

我至今仍记得我们当时住在他在梅尔罗斯的小房子里面，我们在那吸食了很多大麻。