分类的

International classification of diseases is the standardized classification of medical information that is accepted all over world currently. However, there are still many problems of ICD in our country. The quality of ICD should be promoted and improved. Reinforcing the knowledge training of ICD in doctors, professional training of ICD and the sense of responsibility training in codifier is an important way to improve the quality of ICD.

国际疾病分类是目前国际公认的卫生信息标准分类，但是由于我国的ICD分类工作开展的时间还不是很长，推广还不够广泛和深入，目前我国应用ICD分类还存在很多问题，ICD分类质量有待进一步提高和完善，加强临床医师的ICD分类知识培训和编码人员的专业培训及责任心教育是提高ICD分类质量的重要途径。

Using a large data set of 1 894 images,we examine whether the colorspace transformation can increase the compactness of skin distribution and the discriminability between skin and nonskin distributions in fourteen 3D colorspaces and fourteen 2D chrominance planes.

比较结果表明：(1)颜色空间的变换并不能改善肤色紧致性、肤色-非肤色可分辨性以及分类等性能，但RGB及线性变换空间却具有较好的类可分辨性和分类性能；(2)去除亮度信息将明显降低肤色和非肤色之间的可分辨性和分类性能；(3)Bayes决策下的3维SPM的分类性能是最优和空间无关的，而其余分类器则普遍存在类似的"空间偏好性"；(4)同时采用肤色和非肤色模型的分类器的分类性能优于仅使用肤色模型的分类性能。

Algorithm named OVAWWT are presented to improve the equitableness and the precision of classifiers, a multiclassifier of SVMlight named MSVMlight based on the OVAWWT strategy is implemented, and two experiments on CWT100G data set are constructed, one to compare MSVMlight with other classifiers, and the other to compare WRCut strategy with RCut strategy.

多元分类器通常需要在训练时间和分类精度之间折衷。提出了加权阈值策略和一对多分类方法的改进算法 OVAWWT，以增加结果融合的公平性，从而提高分类精度。基于OVAWWT策略和SVMlight二元分类器，实现了基于SVMlight的多元分类器MSVMlight。

Many classifieres for Web document classification are presented. Some of them are more accurate than others, and some provide more interpretable models, but none of them can combine the two beneficial properties.

在现有的Web文档分类器中，有的分类器产生比较精确的分类结果，有的分类器产生更易解释的分类模型，但还没有分类器可以将两个方面的优点结合起来。

Face classification method, face classifier, classification map, face classification program and recording medium having recorded program

标题： 面部分类方法，面部分类装置，分类图，面部分类程序，以及记录该程序的存储介质

In fact, combined classification is not only a trend in pattern recognition field, but an effective method for sure that has been proved. Based on these problems, multiple features of the nephogram data have been extracted in this paper, and according to the theory of information fusion, a classification method of multiple features of nephogram has been constructed. Recurring to the idea of information fusion, the performance of classification has been remarkably enhanced.

另外，针对目前卫星云图分类研究大多集中于利用单一特征集结合分类器进行云图分类，从而忽略了各特征相结合所具有的分类潜能问题，本文提出了一种卫星云图多特征融合分类方法，借助于信息融合的思想，使得分类器的性能得到明显的提升。

Programming to derive fuzzy optimal solutions and fuzzy optimal classification function seta fuzzy set which value is fuzzy optimal classification function and member degree is λ(0≤λ≤ 1,therefore the linear fuzzy support vector machine is constructe...

对于非线性模糊分类问题，引入核函数，类似于线性模糊分类问题得到非线性模糊支持向量分类机。最后构造显示模糊支持向量分类机特点的模糊支持向量集取值为模糊训练点，隶属度为λ(0≤λ≤1的模糊集合。模糊支持向量分类机较好地解决了支持向量机中含有模糊信息的分类问题。

UDI dataset is used to verify the validation of the ABC. Experimental results show that the ABC has higher classification accuracy, with 5％ average improvement, than the naive Bayes one has. Especially, for the dataset containing strong associated attributes, 37％ improvement in accuracy is obtained.

应用UDI数据集对分类器进行了测试，分类结果表明，ABC算法的分类准确率明显高于朴素贝叶斯分类算法，平均提高5％，特别是对属性间有着较强依赖关系的数据集，其分类准确率提高了37％。

In the case study of Plain, the TM image was processed with Tasseled Cap, Principal component analysis and Normalized Difference Vegetation Index extraction, prieror to vegetation classification, The imageries after preprocessing were use to identify the vegetation combined with original TM bands.

对平原地区的植被分类研究，首先对获取的TM影像进行Tasselled Cap处理、PCA处理和NDVI植被指数提取，处理后的各影像与TM原始六个波段影像一起用于植被遥感分类。分类采用监督分类和非监督分类方法，其中TC处理、PCA处理、NDVI影像、TM1-5，7组合影像采用非监督分类，原始TM6波段组合影像和TM3、4、5三波段组合影像采用监督分类。

It transforms the subtractive image from RGB color space to SRG color space. The experiment shows that it is efficient to segment the shadow with the moving vehicles.Secondly, in the vehicle classification module, we process the subtractive image by the morphological filtering and connected component labeling, obtain the figure and position of moving vehicle, and decide the characteristic vectors.At last, two vehicle classifiers are designed, one is the RBFNN classifier based on fuzzy K-means clustering, the other is the RBFNN classifier based on immune algorithm.

在车型分类方面，首先对差分图像作形态学滤波和区域连通处理，得到运动车辆的位置和轮廓，根据分类标准提取出车型分类所需的特征向量，然后分别用两种方法设计出车型分类器，一种是基于模糊K-均值聚类的RBF网络车型分类器，另一种是基于免疫算法的RBF网络车型分类器，通过在相同环境下的实验对比分析，基于免疫算法的RBF网络车型分类器在分类准确性和速度方面都优于基于模糊K-均值聚类的RBF网络车型分类器。

Lugalbanda was a god and shepherd king of Uruk where he was worshipped for over a thousand years.

Lugalbanda 是神和被崇拜了一千年多 Uruk古埃及喜克索王朝国王。

I am coming just now,' and went on perfuming himself with Hunut, then he came and sat.

我来只是现在，'歼灭战perfuming自己与胡努特，那麼，他来到和SAT 。