Data Mining Concepts and Techniques phần 7 ppsx

... efﬁciently. 8 Mining Stream, Time-Series, and Sequence Data Our previous chapters introduced the basic concepts and techniques of data mining. The techniques studied, however, were for simple and structured ... structured data sets, such as data in relational databases, transactional databases, and data warehouses. The growth of data in various complex forms (e.g....

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Data Mining Concepts and Techniques phần 2 ppsx

... for the 2 .7 Summary 97 2 .7 Summary Data preprocessing is an important issue for both data warehousing and data mining, as real-world data tend to be incomplete, noisy, and inconsistent. Data preprocessing includes ... approximation of the original data. PCA is computationally inexpensive, can be applied to ordered and unordered attributes, and can handle sparse dat...

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Data Mining Concepts and Techniques phần 1 potx

... Data Mining 666 11.3.3 Visual and Audio Data Mining 6 67 11.3.4 Data Mining and Collaborative Filtering 670 11.4 Social Impacts of Data Mining 675 11.4.1 Ubiquitous and Invisible Data Mining 675 11.4.2 ... 61 2.3.2 Noisy Data 62 2.3.3 Data Cleaning as a Process 65 2.4 Data Integration and Transformation 67 2.4.1 Data Integration 67 2.4.2 Data Transf...

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Data Mining Concepts and Techniques phần 3 docx

... processing, and data mining. We also introduce on-line analytical mining (OLAM), a powerful paradigm that integrates OLAP with data mining technology. 3.5.1 Data Warehouse Usage Data warehouses and data ... Warehouse and OLAP Technology: An Overview 3.5 From Data Warehousing to Data Mining “How do data warehousing and OLAP relate to data mining? ” In this sec...

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Data Mining Concepts and Techniques phần 4 potx

... include data cube–based data aggregation and attribute- oriented induction. From a data analysis point of view, data generalization is a form of descriptive data mining. Descriptive data mining ... mining describes data in a concise and summarative manner and presents interesting general properties of the data. This is different from predic- tive data mining, whic...

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Data Mining Concepts and Techniques phần 5 ppt

... for age with aGini index of 0. 375 ; the attributes {student} and{ credit rating}arebothbinary,with Gini indexvaluesof0.3 67 and 0.429,respectively. The attribute income and splitting subset {medium, ... scalability. While both SLIQandSPRINThandle disk-resident data sets thatare too large to ﬁt into memory, the scalabilityof SLIQ islimited by the useof its memory-residentdatastructure...

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Data Mining Concepts and Techniques phần 6 ppt

... functions (Hanson and Burr [HB88]), dynamic adjustment of the network topology (Me´zard and Nadal [MN89], Fahlman and Lebiere [FL90], Le Cun, Denker, and Solla [LDS90], and Harp, Samad, and Guha [HSG90] ), and ... such as Duda et al. [DHS01] and James [Jam85], as well as articles by Cover and Hart [CH 67] and Fukunaga and Hummels [FH 87] . Their integration with attribut...

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Data Mining Concepts and Techniques phần 8 potx

... substructures. 9. Metadata mining. Metadata are data about data. Metadata provide semi-structured data about unstructured data, ranging from text and Web data to multimedia databases. It is useful for data ... itemset stream mining; the Hoeffding tree, VFDT, and CVFDT algorithms for stream data classiﬁcation; and the STREAM and CluStream algorithms for stream data...

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Data Mining Concepts and Techniques phần 9 pot

... multimedia data mining focuses on image data mining. Mining text data and mining the World Wide Web are studied in the two subsequent 638 Chapter 10 Mining Object, Spatial, Multimedia, Text, and Web Data where ... closely linked to image analysis and scientiﬁc data mining, and thus many image analysis techniques and scien- tiﬁc data analysis methods can be ap...

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Data Mining Concepts and Techniques phần 10 pot

... constraint-based mining) , the integration of data mining with data warehousing and database systems, the standardization of data mining languages, visualization methods, and new methods for handling ... Data (SIGMOD’99), pages 4 67 478 , Philadelphia, PA, June 1999. [EKS 97] M. Ester, H P. Kriegel, and J. Sander. Spatial data mining: A database approach. In Proc. 19 9...

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