Defining Distance Measures

فهرست عناوین اصلی در این پاورپوینت

فهرست عناوین اصلی در این پاورپوینت

● Defining Distance Measures
● Intuitions behind desirable distance measure properties
● Two Types of Clustering
● Desirable Properties of a Clustering Algorithm
● A Useful Tool for Summarizing Similarity Measurements
● (How-to) Hierarchical Clustering
● K-means Clustering: Step 1
● K-means Clustering: Step 2
● K-means Clustering: Step 3
● K-means Clustering: Step 4
● K-means Clustering: Step 5
● Comments on the K-Means Method
● The K-Medoids Clustering Method
● Partitional Clustering Algorithms

نوع زبان: انگلیسی حجم: 1.87 مگا بایت
نوع فایل: اسلاید پاورپوینت تعداد اسلایدها: 61 صفحه
سطح مطلب: نامشخص پسوند فایل: ppt
گروه موضوعی: زمان استخراج مطلب: 2019/06/14 10:53:48

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عبارات مهم استفاده شده در این مطلب

عبارات مهم استفاده شده در این مطلب

., d, b, similarity, object, two, clustering, peter, s, white, piotr, bob,

توجه: این مطلب در تاریخ 2019/06/14 10:53:48 به صورت خودکار از فضای وب آشکار توسط موتور جستجوی پاورپوینت جمع آوری شده است و در صورت اعلام عدم رضایت تهیه کننده ی آن، طبق قوانین سایت از روی وب گاه حذف خواهد شد. این مطلب از وب سایت زیر استخراج شده است و مسئولیت انتشار آن با منبع اصلی است.

http://www.cs.ucr.edu/~eamonn/teaching/cs235/clustering.ppt

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عبارات پرتکرار و مهم در این اسلاید عبارتند از: ., d, b, similarity, object, two, clustering, peter, s, white, piotr, bob,

مشاهده محتوای متنیِ این اسلاید ppt

مشاهده محتوای متنیِ این اسلاید ppt

organizing data into classes such that there is high intra class similarity low inter class similarity finding the class labels and the number of classes directly from the data in contrast to classification . more informally finding natural groupings among objects. what is clustering also called unsupervised learning sometimes called classification by statisticians and sorting by psychologists and segmentation by people in marketing what is a natural grouping among these objects school employees simpson s family males females clustering is subjective what is a natural grouping among these objects what is similarity the quality or state of being similar likeness resemblance as a similarity of features. similarity is hard to define but… we know it when we see it the real meaning of similarity is a philosophical question. we will take a more pragmatic approach. webster s dictionary defining distance measures definition let o۱ and o۲ be two objects from the universe of possible objects. the distance dissimilarity between o۱ and o۲ is a real number denoted by d o۱ o۲ .۲۳ ۳ ۳۴۲.۷ peter piotr what properties should a distance measure have d a b d b a symmetry d a a constancy of self similarity d a b iif a b positivity separation d a b  d a c d b c triangular inequality peter piotr ۳ d d s d s s i.e. length of s d s۱ ch۱ s۲ ch۲ min d s۱ s۲ if ch۱ ch۲ then else ۱ fi d s۱ ch۱ s۲ ۱ d s۱ s۲ ch۲ ۱ when we peek inside one of these black boxes we see some function on two variables. these functions might very simple or very complex. in either case it is natural to ask what properties should these functions have intuitions behind desirable distance measure properties d a b d b a symmetry otherwise you could claim alex looks like bob but bob looks nothing like alex. d a a constancy of self similarity otherwise you could claim alex looks more like bob than bob does. d a b iif a b positivity separation otherwise there are objects in your world that are different but you cannot tell apart. d a b  d a c d b c triangular inequality otherwise you could claim alex is very like bob and alex is very like carl but bob is very unlike carl. two types of clustering hierarchical partitional algorithms construct various partitions and then evaluate them by some criterion we will see an example called birch hierarchical algorithms create a hierarchical decomposition of the set of objects using some criterion partitional desirable properties of a clustering algorithm scalability in terms of both time and space ability to deal with different data types minimal requirements for domain knowledge to determine input parameters able to deal with noise and outliers insensitive to order of input records incorporation of user specified constraints interpretability and usability a useful tool for summarizing similarity measurements in order to better appreciate and evaluate the examples given in the early part of this talk we will now introduce the dendrogram. the similarity between two objects in a dendrogram is represented as the height of the lowest internal node they share. bovine .۶۹۳۹۵ spider monkey .۳۹ gibbon .۳۶ ۷۹ orang .۳۳۶۳۶ gorilla .۱۷۱۴۷ chimp .۱۹۲۶۸ human .۱۱۹۲۷ . ۸۳۸۶ . ۶۱۲۴ .۱۵ ۵۷ .۵۴۹۳۹ there is only one dataset that can be perfectly clustered using a hierarchy… business economy b۲b finance shopping jobs aerospace agriculture… banking bonds… animals apparel career workspace note that hierarchies are commonly used to organize information for example in a web portal. yahoo’s hierarchy is manually created we will focus on automatic creation of hierarchies in data mining. pedro portuguese petros greek peter english piotr polish peadar irish pierre french peder danish peka hawaiian pietro italian piero italian alternative petr czech pyotr russian cristovao portuguese christoph german christophe french cristobal spanish cristoforo italian kristoffer scandinavian krystof czech christopher english miguel portuguese michalis greek michael english mick irish a demonstration of hierarchical clustering using string edit distance piotr pyotr petros pietro pedro pierre piero peter peder peka peadar michalis michael miguel mick cristovao christopher christophe christoph crisdean cristobal cristoforo kristoffer krystof piotr pyotr petros pietro pedro pierre piero peter peder peka peadar pedro portuguese spanish petros greek peter english piotr polish peadar irish pierre french peder danish peka hawaiian pietro italian piero italian alternative petr czech pyotr russian hierarchal clustering can sometimes show patterns that are meaningless or spurious for example in this clustering the tight grouping of australia anguilla st. helena etc is meaningful since all these countries are former uk colonies. however the tight grouping of niger and india is completely spurious there is no connection between the two. the flag of niger is orange over white over green with an orange disc on the central white stripe symbolizing the sun. the orange stands the sahara desert which borders niger to the north. green stands for the grassy plains of the south and west and for the river niger which sustains them. it also stands for fraternity and hope. white generally symbolizes purity and hope. the indian flag is a horizontal tricolor in equal proportion of deep saffron on the top white in the middle and dark green at the bottom. in the center of the white band there is a wheel in navy blue to indicate the dharma chakra the wheel of law in the sarnath lion capital. this center symbol or the chakra is a symbol dating back to ۲nd century bc. the saffron stands for courage and sacrifice the white for purity and truth the green for growth and auspiciousness. we can look at the dendrogram to determine the correct number of clusters. in this case the two highly separated subtrees are highly suggestive of two clusters. things are rarely this clear cut unfortunately outlier one potential use of a dendrogram is to detect outliers the single isolated branch is suggestive of a data point …

کلمات کلیدی پرکاربرد در این اسلاید پاورپوینت: ., d, b, similarity, object, two, clustering, peter, s, white, piotr, bob,

این فایل پاورپوینت شامل 61 اسلاید و به زبان انگلیسی و حجم آن 1.87 مگا بایت است. نوع قالب فایل ppt بوده که با این لینک قابل دانلود است. این مطلب برگرفته از سایت زیر است و مسئولیت انتشار آن با منبع اصلی می باشد که در تاریخ 2019/06/14 10:53:48 استخراج شده است.

http://www.cs.ucr.edu/~eamonn/teaching/cs235/clustering.ppt

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