data mining concepts techniques ppt han kamber

... data mining regarding data mining methodology and user interaction issues.Answer: Challenges to data mining regarding data mining methodology and user interaction issues include the lowing: mining ... performance of the data mining system precompu-• Tight coupling: The database or data warehouse system is fully integrated as part of the data miningsystem and thereby provides optimized data mining query ... amount of data (such as a few hundred tuple data set)? Answer: One challenge to data mining regarding performance issues is the efficiency and scalability of data miningalgorithms Data mining algorithms

Ngày tải lên: 16/10/2021, 15:40

... 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, ... algorithms have some mechanisms for handling noisy or missing data,this step can help reduce confusion during learning Relevance analysis: Many of the attributes in the data may be redundant ... can handle categorical and continuous-valued attributes Both algorithms propose presorting techniques on disk-resident datasets that are too large to fit in memory Both define the use of new data

Ngày tải lên: 08/08/2014, 18:22

... requirements of clustering indata mining: Scalability: Many clustering algorithms work well on small data sets containing fewer than several hundred data objects; however, a large database may contain ... branches reflectremov-ing noise in the data Early decision tree algorithms cally assume that the data are memory resident—a limitation to data mining on large typi-databases Several scalable algorithms, ... selected attributes or features Data clustering is under vigorous development Contributing areas of research includedata mining, statistics, machine learning, spatial database technology, biology,

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 ... tasks as well.Thus, frequent 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, ... essential role in mining associations, correlations, and many other interesting relationships among data.Moreover, it helps in data classification, clustering, and other data mining tasks as well.Thus,

Ngày tải lên: 08/08/2014, 18:22

... Sequence Data Our previouschapters introduced the basic concepts and techniques of data mining The techniques studied, however, were for simple and structured data sets, such as data in relationaldatabases, ... as a preprocessing tool for data preparation for other data mining tasks 7.13 Data cubes and multidimensional databases contain categorical, ordinal, and numerical data in hierarchical or aggregate ... of data collection 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

Ngày tải lên: 08/08/2014, 18:22

... and Han[CYH05] A method for parallel mining of closed sequential patterns was proposedby Cong, Han, and Padua [CHP05] Data mining for periodicity analysis has been an interesting theme in data mining.Özden, ... Domingos [HSD01] to handle concept drift in time-changing data streams Wang, Fan, Yu, and Han proposed an ensemble classifier to mineconcept-drifting data streams [WFYH03] Aggarwal, Han, Wang, and ... Chen, Dong, Han, et al.[CDH+02] in their study of multidimensional regression analysis of time-series datastreams MAIDS (Mining Alarming Incidents from Data Streams), a stream data miningsystem

Ngày tải lên: 08/08/2014, 18:22

... 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 ... mining focuses on image data mining.Mining text data and mining the World Wide Web are studied in the two subsequent Trang 13sections Here we introduce multimedia data mining methods, including

Ngày tải lên: 08/08/2014, 18:22

... content mining, Weblog mining, anddata mining services on the Internet will become one of the most important andflourishing subfields in data mining Distributed data mining: Traditional data mining ... com-Visual data mining integrates data mining and data visualization in order to discover implicit and useful knowledge from large data sets Forms of visual data mining include data visualization, data ... data mining result visualization, data mining process visu-alization, and interactive visual data mining Audio data mining uses audio signals to indicate data patterns or features of data mining

Ngày tải lên: 08/08/2014, 18:22

... 1Chapter 2 Preprocessing Data In the real world of data-mining applications, more effort is expended preparing data than applying a prediction program to data Data mining methods are quite capable ... application data and the data mining methods Some data mining methods are much faster than others Some have embedded feature selection techniques that are inseparable from the prediction method The techniques ... standard-form model is a data presentation that is uniform and effective across a wide spectrum of data mining methods and supplementary data-reduction techniques Its model of data makes explicit

Ngày tải lên: 14/08/2014, 02:21

... Yasir Khan Page 1 of 11 Data Mining Process, Techniques, Tools & Examples What is Data Mining? Data mining is looking for hidden, valid, and potentially useful patterns in huge data sets Data ... and Spatial databases • Heterogeneous and legacy databases • Multimedia and streaming database • Text databases • Text mining and Web mining Trang 2Ahmed Yasir Khan Page 2 of 11 Data Mining Implementation ... graphical techniques It offers effective data handling and storage facility Oracle Data Mining: Oracle Data Mining popularly knowns as ODM is a module of the Oracle Advanced Analytics Database This Data

Ngày tải lên: 09/09/2022, 10:29

... Automatic cluster detection is an undirected data mining technique that can be used to learn about the structure of complex databases By breaking com­ plex datasets into simpler clusters, automatic ... focused on extracting every last bit of information out of a few hundred data points In data mining applications, the volumes of data are so large that statistical con­ cerns about confidence and accuracy ... reasonable database that purports to be about customers should have this data readily accessible Of course, marketing databases are rarely simple There are two challenges with these concepts The

Ngày tải lên: 14/08/2014, 11:21

... (ECSI, ACST) useful basis as needed by managers of business enterprises in highly charged, rapidly changing niche markets like the fast food industry gauge the service quality of their own operations ... to extension of study to other industries, cultures will help to improve service quality and enhance growth through increased consumerism

Ngày tải lên: 22/12/2013, 02:17

... 1Data Mining Cluster Analysis: Advanced Concepts and Algorithms Lecture Notes for Chapter 9 Introduction to Data Mining by Tan, Steinbach, Kumar © Tan,Steinbach, Kumar Introduction to Data Mining ... Introduction to Data Mining 9 Graph-Based Clustering: Sparsification The amount of data that needs to be processed is drastically reduced – Sparsification can eliminate more than 99% of the ... self-similarity One of the areas of application is spatial data Trang 15© Tan,Steinbach, Kumar Introduction to Data Mining 15 Characteristics of Spatial Data Sets • Clusters are defined as densely populated

Ngày tải lên: 15/03/2014, 09:20

... scoring, census data, 94–95 gathering, 109–110 people most influenced by, 106–107 messages, selecting appropriate, Business Modeling and Data Mining Data Preparation for Data Mining Trang 20recall ... hazards, 410–411 Trang 6D data marts, 485, 491–492 Trang 7Data Preparation for Data Mining Trang 8deep intimacy, customer relationships, data selection, 62–63 Trang 9E Trang 10F F tests (Ronald ... Trang 16235–237 coverage of values, 232–233 data preparation categorical values, 239–240 Trang 17O Occam’s Razor, 124–125 ODBC (Open Database Open Database Connectivity 433–435 P parallel coordinates,

Ngày tải lên: 21/06/2014, 04:20

... development, 198–203 Data mining software classification trees, 98 Data preparation for modeling See Preparing data for modeling Data requirements review and evaluation, 187–188 Data sources selecting, ... alternate data sets, 130–134, 221 Scoring a new file, 151–161 Selecting data for modeling, 36–44 for customer models, 40–42 prospect data, 37–40 for risk models, 42–44 Selecting data sources See Data ... selecting data sources, 25–48 setting the objective, 3–24 Population or market changes, 152, 153–154, 155 Predictive models, 4 5 207 Preparing data for modeling, 51–70 accessing the data, 51–54

Ngày tải lên: 21/06/2014, 04:20

... 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 ... 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 ... details of specific data mining techniques are left for later chapters Prospecting Prospecting seems an excellent place to begin a discussion of business appli­ cations of data mining After all,

Ngày tải lên: 21/06/2014, 04:20

... valuable a typical channel A customer is than a typical channel B customer—a figure that is as valuable as the per-response measures often used to rate channels cost-Data Mining for Customer ... tenures than for others The chance that a customer will survive to reach some more distant future date can be calculated from the intervening hazards Lessons Learned The data mining techniques ... known Most of the directed data mining techniques discussed in this book can be used to build a classification model to assign people to segments based on available data All that is needed is

Ngày tải lên: 21/06/2014, 04:20

... applied to data These patterns can be turned into new features of the data, for use in conjunction with other directed data mining techniques Trang 4Automatic Cluster Detection The data mining techniques ... patterns, but the excess The data may contain so much complex structure that even the best data mining techniques are unable to coax out meaningful patterns When mining such a database for the answer ... characteristics that can be used for further mining Some data and data mining problems naturally involve links As the two case studies about telephone data show, link analysis is very useful for

Ngày tải lên: 21/06/2014, 04:20

... hundred data points In data mining applications, the volumes of data are so large that statistical con­cerns about confidence and accuracy are replaced by concerns about manag­ing large volumes of data ... 2Automatic cluster detection is an undirected data mining technique that can be used to learn about the structure of complex databases By breaking com­ plex datasets into simpler clusters, automatic ... reasonable database that purports to be about customers should have this data readily accessible Of course, marketing databases are rarely simple There are two challenges with these concepts The

Ngày tải lên: 21/06/2014, 04:20

... data mining, though, are the unknown ones Sometimes, data problems are hidden by intervening systems In particular, some data warehouse builders abhor missing data So, in an effort to clean data, ... of the production data mining environment ■■ A business case for investing in data mining and customer analytics Even when the decision has already been made to invest in data mining, the proof-of-concept ... Chapter 17 Working with data is a critical part of the data mining process What does the data mean? There are many ways to answer this question—through written documents, in database schemas, in

Ngày tải lên: 21/06/2014, 04:20