... BASED DATAMINING TECHNIQUESThe objective of datamining is to extract valuable information from one’s data, to discover the ‘hiddengold’. In Decision Support Management terminology, datamining ... one search for patterns of information in data (Parsaye, 1997).Figure 2: Rule Induction process Data mining techniques are based on data retention and data distillation. Rule induction models ... process.REFERENCES[1] Akeel Al-Attar, 1998, DataMining – Beyond Algorithms’, http://www.attar.com/tutor /mining. htm.[2] Berry, J. A. Michael; Linoff, Gordon, 1997, DataMining Techniques: For Marketing,...
... Series Data Series data differs from the forms of data so far discussed mainly in the way in which the data enfolds the information. The main difference is that the ordering of the data ... reason that series data has to be prepared differently from nonseries data. There is a large difference between preparing data for modeling and actually modeling the data. This book focuses ... Modeling Series Data Given these tools for describing series data, how do they help with preparing the data for modeling? There are two main approaches to modeling series data. One uses...
... optimized mining toolset, could not deal with a multiterabyte, 7000+ variable data set required on one mining project. Another reason that high dimensionality presents difficulties for mining ... series data. Data visualization is a broad field in itself, and there are many highly powerful tools for handling data that have superb visualization capability. For small to moderate data sets, ... like. Does one of them seem to fit some underlying trend in the data? If so, subtract it from the data. When graphed, does the data fit the horizontal axis better? If yes, fine. If no, keep trying....
... the mining tool the customer had selected, causing repeated mining software failures and system crashes during mining. The data reduction methodology described above reduced the data ... density manifold stability. But here is where data preparation steps into the data survey. The data survey (Chapter 11) examines the data set as a whole from many different points of view. ... rather than data preparation? Data preparation concentrates on transforming and adjusting variables’ values to ensure maximum information exposure. Data surveying concentrates on examining a...
... do with data mining? The whole purpose of the data survey is to help the miner draw a high-level map of the territory. With this map, a data miner discovers the general shape of the data, as ... can be used to examine data as instances, data as variables, the data set as a whole, and various parts of a data set. Entropy and mutual information are used to evaluate data in many ways. Some ... Such data has a perspective. When mining perspectival data sets, it is very important to use nonperspectival test and evaluation sets. With the best of intentions, the miningdata has...
... 11.4.1 Confidence and Sufficient Data A data set may be inadequate for mining purposes simply because it does not truly represent the population. If a data set doesn’t represent the population ... properly part of the data survey. The survey only looks at and measures the data set presented. While it provides information about the data set, it does not manipulate the data in any way, exactly ... of the instances can be assembled into a data set, and that data set examined for similarity to the training data set, but that only tells you that the data set now assembled was or wasn’t drawn...
... statisticians and data miners still have different philosophical approaches to modeling from data. 12.1.3 DataMining vs. Exploratory Data Analysis Exploratory data analysis (EDA) ... try data mining, a new discipline to her, but one that had received good reviews in the business press. How did the datamining project differ from the statistical approach? Data mining ... relationships from this data that are then to be applied to other similar data. Whatever can be discovered in this data is sufficient, since it works in this data set, and there is no other data set to...
... test data set (top) and an 85.8283% accuracy in the test data for the prepared data set (bottom). 12.4 Practical Use of Data Preparation and Prepared Data How does a miner use data ... working with the data. When the data is easy to model, better models come out faster, which is the technical purpose of data preparation. How does data preparation make the data easier to work ... Data preparation looked at here has dealt with data in the form collected in mainly corporate databases. Clearly this is where the focus is today, and it is also the sort of data on which data...
... what does data preparation alone achieve in this data set? In order to demonstrate that, we will look at two models of the data one on prepared data, and the other on unprepared data. ... Data preparation looked at here has dealt with data in the form collected in mainly corporate databases. Clearly this is where the focus is today, and it is also the sort of data on which data ... datamining tools and data modeling tools focus. The near future will see the development of automated data preparation tools for series data. Approaches for automated series data preparation...
... required for mining distributed data, handling the meta -data and the mappings required for mining the distributed data. Spatial database systems involve spatial data - that ... algorithms and is termed distributed data mining [51].Traditional data mining algorithms require all data to be mined in a single,centralized data warehouse. A fundamental challenge ... 8.Multimedia data mining, including text mining, image mining, and Web min-ing, is dealt with in Chapter 9. Finally, certain aspects of Bioinformatics, asan application of data mining, ...
... Introduction to Data Mining 11.1 Introduction 11.2 Knowledge Discovery and Data Mining 51.3 Data Compression 101.4 Information Retrieval 121.5 Text Mining 141.6 Web Mining 151.7 ... actual data for mining. This also increases the mining efficiency by reducingthe time required for mining the preprocessed data. Data preprocess-ing involves data cleaning, data transformation, ... multimedia data exploration, data mining should no longer be restricted to the mining of knowledge fromlarge volumes of high-dimensional datasets in traditional databases only....
... Implementing a DataMining Process Using Office 2007 187Introducing the DataMining Client 188Importing Data Using the DataMining Client 189 Data Exploration and Preparation 190Discretizing Data with ... Data Mining 413 Mining Aggregated Data 414OLAP Pattern Discovery Needs 415OLAP Mining versus Relational Mining 415Building OLAP Mining Models Using Wizards and Editors 417Using the DataMining ... 584Exploring New DataMining Frontiers and Opportunities 585Further Reference 586Microsoft DataMining 586General DataMining 586Appendix A: Data Sets 589MovieClick Data Set 589Voting Records Data...