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classification statistic相关的网络例句

查询词典 classification statistic

与 classification statistic 相关的网络例句 [注:此内容来源于网络,仅供参考]

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A study of space object classification and statistic analysis based on database[D].

基于数据库的空间目标分类方法及统计分析研究[D]。

Conception and classification of fire statistic are introduced.

本文介绍了火灾统计概念与火灾统计分类。

The conventional classification methods are hard classification based on the spectral statistic features of the pixels.

这些土地利用类型的波谱特征为进行土地利用分类提供了波谱理论基础。

But under limited training sample size, increased dimension of remote sensing data means decreased samples/dimension ratio, which can lead to low classification accuracy if common statistic based pattern classification methods were used.

但在有限训练样本条件下,遥感数据维数的增高使样本/维数比率大大降低,采用常规的统计模式识别方法反而无法得到较好的分类结果。

On the basis of the optimizing program,the microcomputer output of arranging the order of parts,the statistic of the classification of part names and the statistic of characteristic information of parts,and the classification of part groups using BASIC-Ⅱ language are pre- sented.

本文提出了实施成组技术中采用分类编码对产品零件分组的方法,分析了零件组特征矩阵制定的原则,在优化程序的基础上,提供了采用BASIC-Ⅱ语言的关于零件排序、零件名称类别及特征信息统计、零件分组的计算机输出结果。

The popular methods of remote sensing image classification have been generally analyzed and summarized. And the main methods are classification based on statistic, neural network classification, fuzzy classification, decision tree classification, expert system classification. Finally, the characters of each method have been summarized.

现综合分析了目前主要的遥感图像分类方法,将遥感图像分类方法归纳为:基于传统统计分析的分类方法、神经网络分类方法、模糊分类方法、决策树分类方法、专家系统分类方法,并对各种方法的应用情况进行了综述,并总结出各种分类方法应用特点。

New model utilizes grid computing technology,plans as a whole of network computing resources,combines with statistic classification advantage of support vector machine in finite sample space,probes into application of grid computation technology in image classification.

为了充分利用网格技术分布式、高性能、协同共享的能力,设计了一种基于网格和支持向量机的分布式图像分类器模型,采用网格计算技术,统筹网络运算资源,结合支持向量机在有限样本统计分类中的优势,探索网格技术在图像分类中的应用。

In the first approach the metadata extraction is viewed as a classification problem. Three statistic classification models, including Support Vector Machines, Perceptron with Uneven Margins, and Maximum Entropy are studied. The approach suffers from the problems of ignoring the variance in lengths of documents and ignoring the dependency of text units within documents. To solve the problems, our second approach takes the metadata extraction as a sequence data labeling problem and makes full use of the sequential information.

论文首先研究了基于分类的元数据抽取方法,考察了支持向量机、非对称间隔感知机和最大熵模型在ADME中的应用;然后针对分类方法中存在的忽略文档之间的差异、不考虑文档上下文等问题,提出了基于序列数据标注模型的抽取方法,并结合最大熵马尔可夫模型、投票感知机模型和条件随机场模型进行了研究;最后本文根据前两种方法的设计思想和优缺点,研究提出一种新的结构预测模型—— CDASP(Coordinate Descent Algorithm for Structure Prediction),并将其应用于元数据的自动抽取中。

Applling the key techniques of text topics classification to text sentiment classification In this paper, using three kinds feature selection methods (information gain, mutual information and chi-square statistic), and two kinds probability computer, and support vector machine to construct the classifier, text sentiment classification are studied.

本文采用了信息增益、互信息和x~2统计三种特征选择方法以及布尔和频率两种概率估算方法,对文本情感倾向分类进行了实验研究,选择支持向量机技术构造分类器。

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