Classification
生物的界级分类(classification.
生物的界级分类（classification of kingdoms oforganisms）根据生物的基本结构特点、特别是根据生物的演化概况所进行的各种“界”级分类系统。
随着科学的发展，历史上曾先后出现过多种生物界级分类系统，主要有以下几种：（1）林奈的两界系统（1735），包括植物界和动物界；（2）海克尔的三界系统（1866年），包括原生生物界（Kingdom protista）、植物界和动物界；（3）李代尔（G.F.Leedale）的四界系统（1974），包括原核界（Kingdom Monera）（细菌、蓝藻）真菌界（Kingdom Fungi）、植物界和动物界；（4）魏泰克（R.H.Whittaker）的五界（1969），包括原核界、原生生物界、真菌界、植物界和动物界；（5）胡先骕的二总界系统（1965），包括始生和胞生两个总界，始生总界（Suprastatus Protobiota）只有病毒界，胞生总界（Suprastatus Cytobiota）包括细菌界（Status Bacteriobion－ta）、粘菌界（Status Myxobionta）、真菌界（Status Myco－bionta）、植物界（Status Phytobionta）和动物界（StatusZoobionta）；（6）陈世骧等的三总界六界分类系统（1979），即：Ⅰ.非细胞总界（Superkingdom Acytonia） 1.病毒界（包括类病毒）Ⅱ.原核总界（SuperkingdomProcaryota） 2.细菌界（Kingdom Mycomonera）3.蓝藻界（Kingdom Phycomonera）Ⅲ.真核总界（Superkingdom Eucaryota） 4.植物界（Kingdom Plantae）5.真菌界（Kingdom Fungi）6.动物界（Kingdom Animalia）生物的分界面对着众多的生物，科学家为了便于研究起见，逐将生物分门别类。
7.Classification
4
Choosing a topic
Avoid topics that are colorless, flat, insipid, boring, unimaginative, monotonous and BROAD. They require no thought to write and no thought to read, and they require no effort to forget. Topics with two extremes and a middle position are almost always destined for dullness. Bad idea: intelligent thinkers, unintelligent thinkers, and average thinkers. How about this: academic intelligence (raw IQ), commonsense intelligence (good practical judgment), and street-smart intelligence (cunning)? Be New, Be Original! (free-ranging thinking/free associations) Hairdresser’s customers classified as dogs: some pretty and lovable like the cocker spaniel, some growly and assertive like the doberman, and some feisty and temperamental like the poodle.
Classification: Establishing Groups
写作 classification
About creating categories
Remember the categories of a classification must not overlap or contain items already contained within another entry. Otherwise, the classification will become illogical.
Exercise
Mattresses:queen; twin; firm; double;
Single basis:
size
Exercises: fatigue; swimming; jogging; gymnastics;
Single basis:
field
Churches: Roman Catholic; Baptism; Protestant; Orthodox;
Single basis:
branch
Vacation: Seashore; winter; summer; weekends;
Single basis:
time
Related Expression
About creating categories
Once you are given a topic, you will create categories by organizing elements according to a common feature. Decide how to organize elements of your topic into categories. With your categories created, identify common features of each category.
classification英文的缩写
一、 classification的定义classification是classify的名词形式，指的是将事物或者概念按照一定的标准或者特征进行分类和归类的行为。
在各个领域，classification都有着重要的应用，例如在生物学中对动植物的分类，图书馆中对图书的分类，电子产品中对设备的分类等等。
二、classification的英文缩写1. 在计算机科学中，classification常常被用作机器学习、数据挖掘等领域中的重要概念。
在这些领域中，classification通常被表示为"class."或者"cls."的缩写形式。
在Python语言的机器学习库scikit-learn中，classification模块就被命名为"sklearn.classification"。
2. 在图书馆学中，classification系统也有着特定的英文缩写形式。
我们熟知的图书馆分类系统中的Dewey Decimal Classification就常被简写为"DDC"。
3. 在医学领域，classification的英文缩写通常是"ICD"，全称为"International Classification of Diseases"，即国际疾病分类。
ICD 被世界卫生组织用于统计、分析和比较全球范围内的疾病数据，在国际上具有重要的影响力。
4. 在商业和市场营销领域，classification常常被简写为"class."或者"cls."。
对用户进行分类分析，以便进行精准营销的方法就被称为"consumer classification"。
5. 在法律领域，classification的英文缩写为"class."或者"cls."，主要用于法律文件或者文件分类系统中。
Classification
Rules of classification
Apply our principle of classification consistently Apply our principle of classification thoroughly Make the categories logically distinct from each other and avoid overlapping of categories
Supporting sentences
The supporting sentences in a classifying paragraph are parallel and are presented by listing. Therefore, generally speaking, the classifying paragraph is also a listing paragraph. we make a list of the items and discuss them one by one. We achieve coherence by using listing words.
Classification
Classification is one of the most useful methods for explaining an object or idea. We break a general class down and group the parts into categories whose members share similar characteristics. With this method, we create order out of confusion and provide a clear overview of the information we offer.
classification-英文写作分类
Reading
On Matters of Love
3. Do people from different cultures express their love in different ways? The appropriate answer to this question is “Yes. People from different cultures do express their love in different ways.” The ways and examples can be many. For instance, Chinese parents express their love through overprotection, while American parents love their children by respecting their individuality. The final conclusion we may draw is that the feeling of love is universal, but the expressions of love is cultural.
Time
Vogue
The Economist
CNN
Ellen Show
Presentation: How and why?
Group Activity
Classify the following films.
The Fast and the Furious Life of Pi
Gone with the Wind
Ludus Mania
Playing hard-to-get game “Ludus”
英语写作 分类手法 classification
Thank you~
20
Exercise
14
Find out what method is used to expand the definition．
Courage is the willingness to take a risk when the outcome is uncertain，and when the risk taken may involve harm，loss，or danger to the one taking it．For example，in a Los Angeles suburb，a twelve－ year－old girl ran into a burning house to rescue her baby brother，pulled him unconscious out of the burning bedroom，and dragged him down the stairs and outside to safety．This was arousing display of courage．The girl had been safe outside the flaming house when she remembered her sleeping brother．Disregarding her personal safety，she plunged into the flaming house to save him．
• The term itself ; • The class to which the term belongs ; • The characteristics that distinguish the term from all others in its class .
classification_英文写作分类
Principle
Delegates at a conference are classified into Europeans, Africans, Canadians, Somalis, Chinese and blacks.
2). Apply your principle consistently and thoroughly, and avoid overlapping.
Group Activity
Read the following passage and complete the second paragraph. Life would be so much easier if everyone learned new information
in exactly the same way. Teachers would know exactly how to present material so that all students would have an equal opportunity to learn. Unfortunately, that just is not the way it works---people are different in many different ways, and one of the ways they differ is in the style of learning that works best for each person.
classification
Class activity: Point out the arrangement of planes. Find out the topic sentence, classification, description and subconclusion.
Four principles must be followed in writing a classification paragraph or essay: A) Consistency B) Completeness C) Avoidance of overlapping D) Balance
Model Pattern
陈述现象In my opinion, 现象 has both advantages
and disadvantages. On the one hand 好处; on the other hand坏处. one of the important advantages is that 好处一 . Besides/Secondly, 好处二. However, 坏处一 . In addition/ To make matters worse,坏处二 . through the above analysis, there is no denying the fact that 现象 has positive aspects as well as negative ones. Taking both of them into account, I suggest that 建议.
When asked about/ when it comes to事物、问题, different people hold different attitudes/views. Some people take it for granted/ believe/claim that观点一 . However, others hold/argue that观点二 . Weighing up these two arguments, I 我的观点 . First and foremost/ To start with/ For one thing/ On the one hand理由一 .拓展句 /例子 . Besides/ In addition/For another thing/ On the other hand,理由二 .拓展句 /例子 . Last but not least/ Finally,理由三 .拓展句 /例子 . From the foregoing, we can safely draw a conclusion/ a natural conclusion can be drawn that重申观点 .
分类功能(Classification)
分类功能(Classification)1. 总揽分类（Classification）的应用非常广泛，基本在SAP的所有模块中都有应用。
通过分类中的自定义特征（Characteristics）来对物料、客户、供应商、文档、批次、检验特性等进行自定义分类，系统通过类类型Class Type来区分不同的应用，譬如类类型001为物料分类，类类型010为供应商分类，类类型022/023为批次分类，不同的类类型操作方式大体相同，下文中以最常见的物料分类为例介绍分类功能。
2. 分类的用途a) 查找对象：分类与搜索帮助集成在一起b) 报表分析：SAP提供一些标准的报表查询；c) 为采购审批、批次管理、可配置物料等功能做准备；3. 物料分类应用a) 概览想象一下，如何从成千上万个产品中找到我们希望的物料，物料分类就是途径之一。
某公司将销售的产品按照以下特征进行分类，用于查找以及进一步分析；根据分类中包含的特征，我们可以用来查找对象，如创建订单、查询库存时查找颜色为红色、适用人群为男的产品，SAP中的搜索帮助中包括了物料分类，也就是说，无论在SAP的何界面，只要可以输入物料的地方，就可以用下面的特征来查找物料。
b) 操作步骤简述；事务代码CT05创建上述六个特征；事务代码CL02创建分类Z100，包括上述六个特征事务代码MM01或者CL20N将分类分配给物料（如Zbatch001,Zbatch002）最终维护结果如下c) 创建特征和分类时的注意点∙特征属性应根据需要设置特征的格式、属性、长度、是否允许多选；系统支持输入大于、小于等符号。
∙值检查值检查时指系统进行检查输入值是否在允许的值中，同时为输入提供搜索帮助，应尽量设置只能从可选值中进行选择，系统支持有四种方法进行限制，如创建特征时输入允许的特征值（如特征Z101）,为了便于输入特征值，系统还支持层次式的特征值，如销售地区，第一层为大区，第二层为省份，第三层为城市，这样选择起来就非常方便。
classification英文写作分类最新PPT课件
Reading
On Matters of Love
3. Do people from different cultures express their love in different ways? The appropriate answer to this question is “Yes. People from different cultures do express their love in different ways.” The ways and examples can be many. For instance, Chinese parents express their love through overprotection, while American parents love their children by respecting their individuality. The final conclusion we may draw is that the feeling of love is universal, but the expressions of love is cultural.
Reading
On Matters of Love
Stage of relationship
Eros Pragma
“I” am erotically attracted to Managing the love affair like a business
Action Barbara
refuses to be a sex object confused at first, then infuriated
Game of Thrones
04Classification(分类)精品PPT课件
•Speed: computational cost involved in generating and using the model •Robustness: ability to make correct prediction using noisy/missing values •Scalability: Ability to construct the classifier given large amounts of data •Interpretability: level of insight provided by the classifier
Classification
1
Classification
•Definition: assign an object to one of several predefined categories
•Given:
• A set of predefined classes • A number of attributes • A learning set
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Error rate: fraction of wrong predictions err_roarte f01 f10
f11 f10 f01 f00
12
Underfitting and Overfitting
•Underfitting: when the model is too simple •Overfitting: when the model is built to tightly fit the training set
model 2. Classification step: uses the model from step 1 to predict the class
recognitionvsclassification，识别和分类的区别
recognitionvsclassification，识别和分类的区别recognition vs classificationThe field of recognition or pattern recognition is concerned with the automatic discovery of regularities in data through the use of computer algorithms and with the use of these regularities to take actions such as classifying the data into different categories. An example of pattern recognition is classification, which attempts to assign each input value to one of a given set of classes. However, pattern recognition is a more general problem that encompasses other types of output as well, for example, regression.⼤意就是：识别是对数据（⽐如图像）进⾏寻找规律、抽取特征，然后应⽤所得到的规律和特征实现某些⽬的（如分类、分割、检测）的过程。
所以分类只是识别的⼀个具体例⼦。
图像识别的定义图像识别，是指利⽤计算机对图像进⾏处理、分析和理解，以识别各种不同模式的⽬标和对象的技术。
图像识别以图像的主要特征为基础的。
每个图像都有它的特征,如字母A有个尖，P有个圈、⽽Y的中⼼有个锐⾓等。
对图像识别时眼动的研究表明，视线总是集中在图像的主要特征上，也就是集中在图像轮廓曲度最⼤或轮廓⽅向突然改变的地⽅，这些地⽅的信息量最⼤。
Classification
Some examples:
Any good library should contain three basic types of materials. There are three kinds of book owners. The fifteen students of this class fall into three groups. The musical instruments can be divided into three main classes according to the way they are played.
Classification
Classification is one of the most useful methods for explaining an object or idea. We break a general class down and group the parts into categories whose members share similar characteristics. With this method, we create order out of confusion and provide a clear overview of the information we offer.
Supporting sentences
The supporting sentences in a classifying paragraph are parallel and are presented by listing. Therefore, generally speaking, the classifying paragraph is also a listing paragraph. we make a list of the items and discuss them one by one. We achieve coherence by using listing words.
classification作文
classification作文英文回答：The classification of objects and concepts is an essential cognitive function that helps us organize and make sense of our world. There are many different ways to classify things, and the most appropriate method depends on the purpose of the classification.One common way to classify objects is by their physical characteristics. For example, we might classify animals by their size, shape, or color. We might also classify plants by their leaves, flowers, or fruit. This type of classification is often used in scientific research, where it can help us identify and understand the relationships between different species.Another way to classify objects is by their function. For example, we might classify tools by their purpose, such as hammers, screwdrivers, and wrenches. We might alsoclassify clothing by its intended use, such as shirts, pants, and dresses. This type of classification is often used in everyday life, as it helps us quickly and easily find the objects we need.We can also classify objects by their abstract properties, such as their value or importance. For example, we might classify tasks by their priority, such as urgent, important, or trivial. We might also classify ideas bytheir originality or creativity. This type ofclassification is often used in decision-making, as it helps us identify the most important or valuable options.No matter what the purpose of the classification, there are certain principles that should be followed to ensure that the classification is accurate and useful. First, the classification should be based on a single, well-defined criterion. Second, the classification should be exhaustive, meaning that it should include all possible categories. Third, the classification should be mutually exclusive, meaning that each category should be clearly distinct from the others.By following these principles, we can create classifications that are both accurate and useful. Classifications can help us organize and understand our world, make decisions, and solve problems.中文回答：分类是人类认知功能中至关重要的环节，它帮助我们组织和理解我们的世界。
classification 英文写作分类.ppt
Illustration
3. How does the author illustrate each category of love? Are there any transitional expressions?
Definition Exemplification Transitions
Steps
Principle
Delegates at a conference are classified into Europeans, Africans, Canadians, Somalis, Chinese and blacks.
2). Apply your principle consistently and thoroughly, and avoid overlapping.
Group Activity
Read the following passage and complete the second paragraph. Life would be so much easier if everyone learned new information
in exactly the same way. Teachers would know exactly how to present material so that all students would have an equal opportunity to learn. Unfortunately, that just is not the way it works---people are different in many different ways, and one of the ways they differ is in the style of learning that works beHale Waihona Puke t for each person.
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Contents
1. Introduction . . . . . . . . 1.1. Motivation . . . . . . . 1.2. Searching the Web . . . 1.3. Search results clustering 1.4. Layout of the thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 11 11 12 12 13 13 14 14 14 15 16 17 18 18 19 19 20 20 20 20 21 21 21 22 22 23 24 25 26 26 27 27 28
Master thesis in COMPUTER SCIENCE
Supervisor dr Nguyen Hung Son Institute of Mathematics Faculty of Mathematics, Informatics and Mechanics Warsaw University
3. Document clustering . . . . . . . . . . . . . . . . . 3.1. General definition . . . . . . . . . . . . . . . . . . 3.1.1. Clustering in Information Retrieval . . . . 3.2. Vector space model and document representation 3.2.1. Document preprocessing . . . . . . . . . . 3.2.2. Weighting scheme . . . . . . . . . . . . . 3.2.3. Similarity measure . . . . . . . . . . . . . 3.2.4. Cluster representation . . . . . . . . . . . 3.3. Clustering algorithms . . . . . . . . . . . . . . . 3.3.1. Hierarchical algorithms . . . . . . . . . . 3.3.2. Partitioning-based . . . . . . . . . . . . . 3.3.3. Optimization criteria . . . . . . . . . . . . 3.3.4. Hard vs. soft assignment . . . . . . . . . 3
2. Searching for information on the Web 2.1. Search engines . . . . . . . . . . . . . 2.1.1. Ranking algorithms . . . . . . 2.2. User interaction . . . . . . . . . . . . . 2.2.1. Query - concept mismatch . . . 2.2.2. Query expansion . . . . . . . . 2.2.3. Ranked list . . . . . . . . . . . 2.3. Search results clustering . . . . . . . . 2.4. Previous work . . . . . . . . . . . . . . 2.4.1. Scather/Gather . . . . . . . . . 2.4.2. Grouper . . . . . . . . . . . . . 2.4.3. Carrot, Carrot 2 Framework . . 2.4.4. Vivisimo . . . . . . . . . . . . . 2.4.5. SHOC, LINGO . . . . . . . . . 2.4.6. AHC . . . . . . . . . . . . . . . 2.4.7. CHCA . . . . . . . . . . . . . .
4. Rough Sets and the Tolerance Rough Set Model . . . . . 4.1. Approximation of concept . . . . . . . . . . . . . . . . . . . 4.1.1. Indiscernibility relation . . . . . . . . . . . . . . . . 4.1.2. Rough membership . . . . . . . . . . . . . . . . . . . 4.1.3. Information Systems . . . . . . . . . . . . . . . . . . 4.2. Generalized approximation spaces . . . . . . . . . . . . . . . 4.2.1. Definition . . . . . . . . . . . . . . . . . . . . . . . . 4.2.2. Approximations . . . . . . . . . . . . . . . . . . . . . 4.3. Tolerance Rough Set Model . . . . . . . . . . . . . . . . . . 4.3.1. Tolerance space of terms . . . . . . . . . . . . . . . . 4.3.2. Enriching document representation . . . . . . . . . . 4.3.3. Extended weighting scheme for upper approximation 5. The Tolerance Rough Set clustering algorithm for search 5.1. Document clustering algorithms based on TRSM . . . . . . 5.1.1. Cluster representation . . . . . . . . . . . . . . . . . 5.1.2. TRSM-based non-hierarchical clustering algorithm . 5.1.3. TRSM-based hierarchical clustering algorithm . . . . 5.2. Clustering search results . . . . . . . . . . . . . . . . . . . . 5.3. The TRC algorithm . . . . . . . . . . . . . . . . . . . . . . 5.3.1. Preprocessing . . . . . . . . . . . . . . . . . . . . . . 5.3.2. Document corpus building . . . . . . . . . . . . . . . 5.3.3. Tolerance class generation . . . . . . . . . . . . . . . 5.3.4. K-means clustering . . . . . . . . . . . . . . . . . . . 5.3.5. Cluster label generation . . . . . . . . . . . . . . . . 5.4. Implementation . . . . . . . . . . . . . . . . . . . . . . . . . 5.4.1. Carrot2 Framework . . . . . . . . . . . . . . . . . . 5.4.2. TRC as a Carrot2 filter component . . . . . . . . . 6. Evaluation, experiments, comparisons . . . . . . . . . . 6.1. Current evaluation methods . . . . . . . . . . . . . . . . 6.1.1. Ground truth . . . . . . . . . . . . . . . . . . . . 6.1.2. User feedback . . . . . . . . . . . . . . . . . . . . 6.2. Our evaluation . . . . . . . . . . . . . . . . . . . . . . . 6.3. Test data collection . . . . . . . . . . . . . . . . . . . . . 6.3.1. Test queries . . . . . . . . . . . . . . . . . . . . . 6.3.2. Data characteristic . . . . . . . . . . . . . . . . . 6.3.3. Effects of terms filtering . . . . . . . . . . . . . . 6.4. Tolerance classes generation . . . . . . . . . . . . . . . . 6.4.1. Size and richness . . . . . . . . . . . . . . . . . . 6.5. Upper approximation enrichment . . . . . . . . . . . . . 6.5.1. Upper approximation of document representation 6.5.2. Inter-document similarity . . . . . . . . . . . . . 6.6. Example of results . . . . . . . . . . . . . . . . . . . . . 6.6.1. Topic generality . . . . . . . . . . . . . . . . . . 6.6.2. Data size . . . . . . . . . . . . . . . . . . . . . . 6.6.3. Number of initial clusters . . . . . . . . . . . . . 6.6.4. Similarity threshold . . . . . . . . . . . . . . . . 6.6.5. Phrase usage . . . . . . . . . . . . . . . . . . . . 4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .