... of the datamining task, the nature of the available data, and the skills and preferences of the data miner. Data mining comes in two flavors—directed and undirected. Directed data mining ... that, on a technical level, the datamining effort is working and the data is reasonably accurate. This can be quite comforting. If the dataand the dataminingtechniques applied to it are powerful ... corporation to improve its marketing, sales, andcustomer support operations through a better understanding of its customers. Keep in mind, however, that the dataminingtechniquesand tools described...
... level data, 96 publications Building the Data Warehouse (Bill Inmon), 474 Business Modeling andDataMining (Dorian Pyle), 60 Data Preparation forDataMining (Dorian Pyle), 75 The Data ... 89–90 metadata repository, 484, 491 methodologies data correction, 72–74 data exploration, 64–68 data mining process, 54–55 data selection, 60–64 data transformation, 74–76 data translation, ... Business Modeling andData Mining, 60 Data Preparation forData Mining, 75 470643 bindex.qxd 3/8/04 11:08 AM Page 619C Index 619 calculations, probabilities, 133–135 call detail databases, 37...
... of the datamining task, the nature of the available data, and the skills and preferences of the data miner. Data mining comes in two flavors—directed and undirected. Directed data mining ... corporation to improve its marketing, sales, andcustomer support operations through a better understanding of its customers. Keep in mind, however, that the dataminingtechniquesand tools described ... cards, and banking, for example. Adding to the deluge of internal data are external sources of demographic, lifestyle, and credit information on retail customers, and credit, financial, and marketing...
... before. The newly discovered relationships suggest new hypotheses to test and the datamining process begins all over again. Lessons Learned Data mining comes in two forms. Directed datamining ... 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 ... 11:10 AM Page 97 Data Mining Applications 97 mining techniques used to generate the scores. It is worth noting, however, that many of the dataminingtechniques in this book can and have been...
... value of their customer data by beginning to track customers from their first response, even before they become customers, and gathering and storing additional information when customers are ... Page 109 Data Mining Applications 109 Start Tracking Customers before They Become Customers It is a good idea to start recording information about prospects even before they become customers. ... Segmenting the Customer Base Customer segmentation is a popular application of datamining with estab-lished customers. The purpose of segmentation is to tailor products, services, and marketing...
... Use customers in California for the challenger and everyone else for the champion. ■■ Use the 5 percent lowest and 5 percent highest value customers for the challenger, and everyone else for ... percent most recent customers for the challenger, and every-one else for the champion. ■■ Use the customers with telephone numbers for the telemarketing cam-paign; everyone else for the direct ... in several areas: ■■ Data miners tend to ignore measurement error in raw data. ■■ Data miners assume that there is more than enough dataand process-ing power. ■■ Datamining assumes dependency...
... common for neural networks are the logistic and the hyperbolic tangent. The major difference between them is the range of their outputs, between 0 and 1 for the logistic and between –1 and 1 for ... generalize and learn from data mimics, in some sense, our own ability to learn from experience. This ability is useful fordata mining, and it also makes neural networks an exciting area for research, ... test set to see how well it performs. 7. Apply the model generated by the network to predict outcomes for unknown inputs. Fortunately, datamining software now performs most of these steps auto-matically....
... detection is used to evaluate editorial zones for a major daily newspaper. Searching for Islands of Simplicity In Chapter 1, where dataminingtechniques are classified as directed or undi-rected, ... the databases encountered in market-ing, sales, andcustomer support are not about points in space. They are aboutpurchases, phone calls, airplane trips, car registrations, and a thousand otherthings ... applied to data. These patterns can be turned into new features of the data, for use in conjunction with other directed datamining techniques. 470643 c11.qxd 3/8/04 11:17 AM Page 355Automatic Cluster...
... censoring. When looking at customerdatafor hazard calculations, both the tenure and the censoring flag are needed. For the customers in Figure 12.7, Table 12.2 shows this data. It is instructive ... Practice Survival analysis has proven to be very valuable for understanding customers and quantifying marketing efforts in terms of customer retention. It provides a way of estimating how long ... cus-tomer 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...
... which datamining technique or techniques to apply depends on the particular datamining task to be accomplished and on the data available for analysis. Before deciding on a datamining technique, ... into a series of datamining tasks and under-stand the nature of the available data in terms of the content and types of the data fields. Formulate the Business Goal as a DataMining Task The ... models, one based on the marketingdataand one based on call detail data. The marketingdata was already summarized at the customer level and stored in an easily accessible database system. Getting...
... preparing, and loading data. These are important and must be a standard and repeatable process, but what is the role of meta data? ã Central control repository for all databasesã Repository fordata ... discuss customer data. This data is used to cross-sell, up-sell, and retain existing customers. And finally, I discuss several types of risk data. This is appropriate for both prospects and customers. Data ... Extracting and staging data from sourcesã Cleaning and aligning data/ exception handlingã Transporting and loading data ã Summarizing data ã Refreshing process and proceduresã Employing meta data...
... various forms of estimated income (inc_est3). I have created three forms for each model: inc_miss, inc_est3, and inc_low. These represent the original form after data clean-up (inc_est3) and two ... I have 22 forms of the variable estimated income. I have 20 continuous forms and 2 categorical forms. I will use logistic regression to find the best form or forms of the variable for the final ... sensitivity level entering, and sls=, which stands for sensitivity level staying. These are the sensitivity levels for variables entering and remaining in the model.proc logistic data= acqmod.model2(keep=active...