... Effect of dataset 151 6.7.2 Effect of pre-processing method and risk factor data 153 6.8 Comparison of Models for Prediction of corVD and anyVD 163 6.9 Effect of Non ... Comparison of DT and rule based methods for selected datasets (AUC) 217 Appendix M: Comparison of DT and rule based methods for selected datasets (MR) 218 xi Appendix N: Comparison of methods and dataset ... Comparison of DT and rule based methods for selected datasets (AUC) 217 Appendix M: Comparison of DT and rule based methods for selected datasets (MR) 218 Appendix N: Comparison of methods and dataset...
... Insourcing DataMining Building an Interdisciplinary DataMining Group Building a DataMining Group in IT Building a DataMining Group in the Business Units What to Look for in DataMining Staff DataMining ... all of them How DataMining Is Being Used Today This whirlwind tour of a few interesting applications ofdatamining is intended to demonstrate the wide applicability of the dataminingtechniques ... Results of the Actions Choosing a DataMining Technique Formulate the Business Goal as a DataMining Task Determine the Relevant Characteristics of the DataData Type Number of Input Fields Free-Form...
... 491–492 data selection contents of, outcomes of interest, 64 data locations, 61–62 density, 62–63 history of, determining, 63 scarce data, 61–62 variable combinations, 63–64 data transformation ... automatic cluster detection, 371–372 documentation data mining, 536–537 historical data as, 61 dumping data, flat files, 594 E EBCF (existing base churn forecast), 469 economic data, useful data sources, ... house-hold level data, 96 publications Building the Data Warehouse (Bill Inmon), 474 Business Modeling and DataMining (Dorian Pyle), 60 Data Preparation forDataMining (Dorian Pyle), 75 The Data Warehouse...
... all of them How DataMining Is Being Used Today This whirlwind tour of a few interesting applications ofdatamining is intended to demonstrate the wide applicability of the dataminingtechniques ... business problem Miningdata to transform the data into actionable information Acting on the information Measuring the results Transform data into actionable information using dataminingtechniques ... Applying DataMining BofA worked with datamining consultants from Hyperparallel (then a datamining tool vendor that has since been absorbed into Yahoo!) to bring a range ofdatamining techniques...
... the Profile? One way of determining whether a customer fits a profile is to measure the similarity—which we also call distance—between the customer and the profile Several dataminingtechniques ... discussion is independent of the dataDataMining Applications miningtechniques used to generate the scores It is worth noting, however, that many of the dataminingtechniques in this book can ... models is the one step of the datamining process that has been truly automated by modern datamining software For that reason, it takes up relatively little of the time in a datamining project 77...
... volumes of data, datamining has the connotation of searching fordata to fit preconceived ideas This is much like what politicians around election time—search fordata to show the success of their ... the data collected by scientists, most of which took the form of continuous measurements In data mining, we encounter continuous data less often, because there is a wealth of descriptive data ... at data The Lure of Statistics: DataMining Using Familiar Tools Looking at Discrete Values Much of the data used in datamining is discrete by nature, rather than contin uous Discrete data...
... there is a formula for the standard error of a difference of propor tions (SEDP): SEDP = p1 ) (1 - p1) (1 - p2) N1 + p2 ) N2 This formula is a lot like the formula for the standard error of a proportion, ... The Lure of Statistics: DataMining Using Familiar Tools Size of Sample The formulas for the standard error of a proportion and for the standard error of a difference of proportions both include ... not resemble another Data mining, on the other hand, must often consider the time component of the data Experimentation is Hard Datamining has to work within the constraints of existing business...
... parameters of the network Preparing the Data Preparing the input data is often the most complicated part of using a neural network Part of the complication is the normal problem of choosing the right data ... diesel engines, fraudulent use of a credit card, or who will respond to an offer for a home equity line of credit—then the training set must have a sufficient number of examples of these rare events ... number of children variable might be mapped as follows: (for children), 0.5 (for one child), 0.75 (for two children), 0.875 (for three children), and so on For cate gorical variables, it is often...
... as the types of outgoing calls, which can then be applied to data These patterns can be turned into new features of the data, for use in conjunction with other directed dataminingtechniques 347 ... lack of patterns, but the excess The data may contain so much complex structure that even the best dataminingtechniques are unable to coax out meaningful patterns When mining such a database for ... same attributes often turn out to be predictive for many different target variables The oft quoted rule of thumb that 80 percent of the time spent on a datamining project goes into data preparation...
... databases often contain data on millions of customers and former customers Much of the statistical background of survival analysis is focused on extracting every last bit of information out of ... Cluster Detection Lessons Learned Automatic cluster detection is an undirected datamining technique that can be used to learn about the structure of complex databases By breaking com plex datasets ... hundred data points In datamining applications, the volumes ofdata are so large that statistical con cerns about confidence and accuracy are replaced by concerns about manag ing large volumes of...
... the testing of a variety ofdataminingtechniques Chapter 16 has advice on selecting datamining software and set ting up a datamining environment One of the goals of the proof -of- concept project ... into dollars The best way to prove the value ofdatamining is with Putting DataMining to Work A SUCCESSFUL PROOF OF CONCEPT? A datamining proof of concept project can be technically successful, ... the pro files to develop retention offers for an outbound telemarketing campaign This description focuses on the datamining aspect of the combined effort The goal of the datamining effort was...
... quantities of real data to use for training sets Consequently, they spent much time and effort trying to coax the last few drops of information from their impoverished datasets—a problem that data ... generate scores, it is easy to forget that a decision tree is actually a collection of rules If one of the purposes of the datamining effort is to gain understanding of the problem domain, it can ... examples of decision trees being used in all of these ways Decision Trees as a Data Exploration Tool During the data exploration phase of a datamining project, decision trees are a useful tool for...
... relationships are all visible in data, and they all contain a wealth of informa tion that most dataminingtechniques are not able to take direct advantage of In our ever-more-connected world ... transactions consists of one or more items, often several dozen at a time So, determining if a particular combination of items is present in a particular transaction may require a bit of effort—multiplied ... size The number of transactions is also very large In the course of a year, a decent-size chain of supermarkets will generate tens or hundreds of millions of transactions Each of these transactions...
... patterns in data and therefore has a firm requirement for clean and consistent data Much of the effort behind datamining endeavors is in the steps of identifying, acquiring, and cleansing the data ... rate data warehouse is a valuable ally Better yet, if the design of the data ware house includes support fordatamining applications, the warehouse facilitates and catalyzes datamining efforts ... specific parts of a business is there—lots and lots of data, somewhere, in some form Data is available but not information—and not the right information at the right time The goal ofdata warehouses...
... set of requirements Building the DataMining Environment The Mining Platform The mining platform supports software fordata manipulation along with datamining software embodying the datamining ... 17.1 shows range characteristics for typical types ofdata used fordatamining TE 542 Table 17.1 Range Characteristics for Typical Types ofData Used forDataMining VARIABLE TYPE TYPICAL RANGE ... destination of much datamining work is reports for management, and the power of graphics should not be underestimated for convincing non-technical users ofdatamining results A datamining tool...
... Undirected datamining is descriptive by nature, so undirected dataminingtechniques are often used for profiling, but directed techniques such as decision trees are also very useful for building profiles ... the Profile? One way of determining whether a customer fits a profile is to measure the similarity—which we also call distance—between the customer and the profile Several dataminingtechniques ... model of these ■■ The test set is used to determine how the model performs on unseen dataDataminingtechniques can be used to make three kinds of models for three kinds of tasks: descriptive profiling,...