data mining techniques and applications pdf

... less data preparation than many other techniques because they are equally adept at handling continuous and categorical vari­ ables Categorical variables, which pose problems for neural networks and ... Time-oriented data does require a lot of data preparation Time series data must be enhanced so that trends and sequential patterns are made visible Decision trees reveal so much about the data to which ... complexity and training set misclassification rate The CART algorithm identifies a set of such subtrees as candidate models These candidate subtrees are applied to the validation set and the tree

Ngày tải lên: 21/06/2014, 21:20

... threshold also implies that: A and B must appear together in at least 10,000 transactions, and, A and C must appear together in at least 10,000 transactions, and, A and D must appear together in ... to which patients? These relationships are all visible in data, and they all contain a wealth of informa­tion that most data mining techniques are not able to take direct advantage of In our ... soda, and window cleaner, the first step calculates the counts for each of these items During the second step, the following counts are created: ■■ Milk and detergent, milk and soda, milk and

Ngày tải lên: 21/06/2014, 21:20

... this requires a data mining group and the infrastructure to support it The Data Mining Group The data mining group is specifically responsible for building models and using data to learn about ... to publish scores, rules, and other data mining results back to the data warehouse and to other applications that need them The data mining infrastructure is logically (and often physically) split ... involved with any IT-based data mining projects Trang 10Building a Data Mining Group in the Business Units The alternative to putting the data mining group where the data and comput­ ers are is to

Ngày tải lên: 21/06/2014, 21:20

... ONLINE SOCIAL NETWORKS: USING DATA- MINING TECHNIQUES AND FUZZY School of Electrical Engineering and Computer Science Faculty of Science and Engineering Queensland University of Technology November ... be developed and customised for a specific application by adopting notions from different disciplines such as statistics, machine learning, and data mining Depending on applications and their limitations, ... interested friends and acquaintances, and to share information, photos, and videos This powerful phenomenon, which captures the structure and dynamics of person-to-person and person-to-technology

Ngày tải lên: 07/08/2017, 15:46

... rules: Watch the game and home team wins and out with friends then beer Watch the game and home team wins and sitting at home then diet soda Watch the game and home team loses and out with friends ... less data preparation than many other techniques because they are equally adept at handling continuous and categorical vari­ables Categorical variables, which pose problems for neural networks and ... Time-oriented data does require a lot of data preparation Time series data must be enhanced so that trends and sequential patterns are made visible Decision trees reveal so much about the data to which

Ngày tải lên: 14/08/2014, 11:21

... Case-Based Data Mining Platform 29 Data mining practice in industry heavily depends on experienced data mining professionals to provide solutions For the rarity of data mining professionals, data mining ... simplify data mining process, reduce the dependency on data mining professional, and shorten business decision time Keywords: Data Mining, Knowledge Reuse, Case-Based Reasoning, Case- Based Data Mining ... of the complexity of data mining process and data mining tools In this paper, we propose a case-based data mining platform, which reuses the knowledge captured in past data mining cases to semi-automatically

Ngày tải lên: 05/11/2019, 14:12

... Henry VIII This special issue of Data Mining and Knowledge Discovery addresses the issue of scaling data mining algorithms, applications and systems to massive data sets by applying high performance ... the data mining group in the centre He has been working on distributed data mining algorithms and systems development He is also working on network infrastructure for global wide data mining applications ... workstations and related technologies, it is becoming more and more common to have the necessary infrastructure for high performance data mining On the other hand, many of the commonly used data mining

Ngày tải lên: 01/06/2014, 09:18

... California based on data that excludes calls to Los Angeles Step Six: Transform Data to Bring Information to the Surface Once the data has been assembled and major data problems fixed, the data must still ... the one step of the data mining process that has been truly automated by modern data mining software For that reason, it takes up relatively little of the time in a data mining project Trang ... series Monthly snapshots of billing informa­tion, usage, contacts, and so on Most data mining algorithms do not understand time series data Signals such as “three months of declining revenue” cannot

Ngày tải lên: 21/06/2014, 04:20

... customer loyalty and customer value as well Trang 16tisticians and data miners The two disciplines are very similar Statisticians and data miners com­monly use many of the same techniques, and statistical ... invented techniques to handle whatever problem was at hand Statisticians are still practical people who use modern techniques as well as the tried and true 123 Trang 17What is remarkable and a ... for prospects and, because it is behavioral in nature rather than sim­ply geographic and demographic, it is more predictive Data mining is used to identify additional products and services that

Ngày tải lên: 21/06/2014, 04:20

... a data mining query language can be used to specify data mining tasks In particular, we examine how to define data warehouses and data marts in our SQL-based data mining query language, DMQL Data ... for time, item, and location are shared between both the sales and shipping fact tables In data warehousing, there is a distinction between a data warehouse and a data mart A data warehouse collects ... form of data cleaning, as well as data reduction In summary, real-world data tend to be dirty, incomplete, and inconsistent Data preprocessing techniques can improve the quality of the data, thereby

Ngày tải lên: 08/08/2014, 18:22

... with data mining technology Data warehouses and data marts are used in a wide range of applications Businessexecutives use the data in data warehouses and data marts to perform data analysis andmake ... respect to datamining functionality and the complexity of the data handled Because data mining involves more automated and deeper analysis than OLAP,data mining is expected to have broader applications ... sense, data mining goes one step beyond traditional on-line analyticalprocessing An alternative and broader view of data mining may be adopted in which datamining covers both data description and data

Ngày tải lên: 08/08/2014, 18:22

... 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 describes ... pattern mining has become an important data mining task and a focusedtheme in data mining research In this chapter, we introduce the concepts of frequent patterns, associations, and relations, and ... Data Cube Computation and Data Generalizationcube computation in MOLAP was proposed in Zhao, Deshpande, and Naughton[ZDN97] Ross and Srivastava [RS97] developed a method for computing sparsedata

Ngày tải lên: 08/08/2014, 18:22

... assuming a small data size Recent data mining research has built onsuch work, developing scalable classification and prediction techniques capable of han-dling large disk-resident data In this chapter, ... such as binning, histogram analysis, and clustering Data cleaning, relevance analysis (in the form of correlation analysis and attributesubset selection), and data transformation are described in ... training setsinclude SLIQ and SPRINT, both of which can handle categorical and continuous-valued attributes Both algorithms propose presorting techniques on disk-resident datasets that are too large

Ngày tải lên: 08/08/2014, 18:22

... Michalski,Carbonell, and Mitchell [MCM83,MCM86], Kodratoff and Michalski [KM90], Shavlikand Dietterich [SD90], and Michalski and Tecuci [MT94] For a presentation of machinelearning with respect to data mining applications, ... be found in Quinlan and Rivest [QR89], Mehta, Agrawal, andRissanen [MRA95], and Rastogi and Shim [RS98] Other methods include Niblett andBratko [NB86], and Hosking, Pednault, and Sudan [HPS97] ... functions(Hanson and Burr [HB88]), dynamic adjustment of the network topology (Me´zardand Nadal [MN89], Fahlman and Lebiere [FL90], Le Cun, Denker, and Solla [LDS90],and Harp, Samad, and Guha [HSG90] ), and

Ngày tải lên: 08/08/2014, 18:22

... basic concepts and techniques of data mining The techniques studied, however, were for simple and structured data sets, such as data in relationaldatabases, transactional databases, and data warehouses ... 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 ... andadvanced database system technologies, and the World Wide Web Therefore, an increas-ingly important task in data mining is to mine complex types of data Furthermore, manydata mining applications

Ngày tải lên: 08/08/2014, 18:22

... retrieval and multidimensional indexing methods, should be integrated with data generalization and data mining techniques to achieve satisfactory results Techniques for mining such data are further ... component of such databases can be generalized, and how the generalized data can be used for multidimensional data analysis and data mining 10.1.1 Generalization of Structured Data An important ... object-relational and object-oriented databases is their capability of storing, accessing, and modeling complex structure-valued data, such as set- and list-valued data and data with nested structures

Ngày tải lên: 08/08/2014, 18:22

... in spatial databases Such mining demands an integration of data mining with spatial database technologies It can be used for standing spatial data, discovering spatial relationships and relationships ... spatial data mining techniques due to the huge amount under-of spatial data and the complexity of spatial data types and spatial access methods “What about using statistical techniques for spatial data ... sensing data, and computer tomography It is important to explore data mining in raster or image databases Methodsfor mining raster and image data are examined in the following section regarding themining

Ngày tải lên: 08/08/2014, 18:22

... cross cultural analysis  Managerial implications and recommendations  Style: scientific and statistical -7- 18/01/2006 Ulrich Öfele 3. Methodology and Instruments:  Customer Satisfaction Survey ... service quality and enhance growth through increased consumerism -2- 18/01/2006 Ulrich Öfele Overview : 1. Authors and outline of the text 2. Research objectives 3. Methodology and Instruments 4. ... of same methods with which SatPers and SatSett were originally derived  Restaurants: Burger King, Checkers, Kentucky Fried Chicken, McDonald’s Taco Bell and Wendy’s (cross national)  Questions...

Ngày tải lên: 22/12/2013, 02:17