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 relationaldatabases, transactional databases, and data warehouses. The growth of data in variouscomplex forms (e.g., semi-structured and unstructured, spatial and ... telecommu-nications data, transaction data from the retail industry, and data from electric powergrids. Traditional OLAP and data mining methods typically require multiple scans ofthe data and are therefore...

Data Mining Concepts and Techniques phần 2 ppsx

... for the2 .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 preprocessingincludes ... approximation of the original data. PCA is computationally inexpensive, can be applied to ordered and unorderedattributes, and can handle sparse data and skewed data. Multidimensional data of more than ... (inclusive).2.3 Data Cleaning 652.3.3 Data Cleaning as a ProcessMissing values, noise, and inconsistencies contribute to inaccurate data. So far, we havelooked at techniques for handling missing data and...

Data Mining Concepts and Techniques phần 1 potx

... Data Mining 66611.3.3 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 ... 612.3.2 Noisy Data 622.3.3 Data Cleaning as a Process 652.4 Data Integration and Transformation 67 2.4.1 Data Integration 67 2.4.2 Data Transformation 70 2.5 Data Reduction 72 2.5.1 Data Cube Aggregation ... Reference Data in Enterprise Databases: Binding Corporate Data to the Wider WorldMalcolm Chisholm Data Mining: Concepts and Techniques Jiawei Han and Micheline KamberUnderstanding SQL and Java...

Data Mining Concepts and Techniques phần 3 docx

... processing, and data mining. We also introduce on-line analytical mining (OLAM), a powerful paradigm thatintegrates OLAP with data mining technology.3.5.1 Data Warehouse Usage Data warehouses and data ... Warehouse and OLAP Technology: An Overview3.5From Data Warehousing to Data Mining “How do data warehousing and OLAP relate to data mining? ” In this section, we study theusage of data warehousing ... Chapter 3 Data Warehouse and OLAP Technology: An Overview data by OLAP operations), and data mining (which supports knowledge discovery).OLAP-based data mining is referred to as OLAP mining, or...

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, which analyzes data in order to ... Canada 8-12 -76 3511 Main St., Richmond 6 87- 4598 3. 67 Scott Lachance M CS Montreal, Que, Canada 28 -7- 75 345 1st Ave., Vancouver 253-9106 3 .70 Laura Lee F Physics Seattle, WA, USA 25-8 -70 125 Austin...

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 intomemory, the scalabilityof SLIQ islimited by the useof its memory-residentdatastructure.SPRINT removes ... even for real-world data. RainForest has techniques, however, for handlingthe case where the AVC-group does not ﬁt in memory. RainForest can use any attributeselection measure and was shown to...

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 attribute-weighting and the pruning of noisy ... complexity (Laskey and Mahoney [LM 97] ),have prompted the exploration of hierarchical and composable Bayesian models (Pfef-fer, Koller, Milch, and Takusagawa [PKMT99] and Xiang, Olesen, and Jensen [XOJ00]).These...

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 data- bases. It is useful for data ... itemsetstream mining; the Hoeffding tree, VFDT, and CVFDT algorithms for stream data classiﬁcation; and the STREAM and CluStream algorithms for stream data clustering.A time-series database consists ... of sequence data include cus-tomer shopping sequences, Web clickstreams, and biological sequences.548 Chapter 9 Graph Mining, Social Network Analysis, and Multirelational Data Mining graph....

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 subsequent638 Chapter 10 Mining Object, Spatial, Multimedia, Text, and Web Data where ... closely linked to imageanalysis and scientiﬁc data mining, and thus many image analysis techniques and scien-tiﬁc data analysis methods can be applied to image data mining. The popular use of the ... data, and computertomography. It is important to explore datamining inraster or image databases.Methodsfor mining raster and image data are examined in the following section regarding themining...

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 meth-ods 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 97 Int. Symp. Large Spatial Databases ... 1998.[BS97a] D. Barbara and M. Sullivan. Quasi-cubes: Exploiting approximation in multidimen-sional databases. SIGMOD Record, 26:12– 17, 19 97. [BS97b] A.BersonandS.J.Smith.DataWarehousing,DataMining,andOLAP.McGraw-Hill,19 97. [BST99]...

Xem thêm