... test_ct = 5e6;4 double data[ ] = { 30, 86,5 24, 38 };6 apop _data *testdata = apop_line_to _data( data,0,2,2);7 for (i = 0; i< test_ct; i++)8 apop_test_fisher_exact(testdata);9 }Listing 1.5 ... times. Online source:.1 test_ct <− 5e62 data <− c( 30, 86,3 24, 38 )4 testdata<− matrix (data, nrow=2)5 for (i in 1:test_ct){6 fisher.test(testdata)7 }Listing 1.6 R code to do the same ... like the debugger and profiler• Methods for reliability testing functions and making them more robust• Databases, and how to get them to produce data in the format you need• Talking to external...
... that, on a technical level, the datamining effort is working and the data is reasonably accurate. This can be quite comforting. If the data and the dataminingtechniques applied to it are powerful ... resolve these issues. Datamining can help make more informed decisions. It can suggest tests to make. Ultimately, though, the business needs What Is Data Mining? Data mining, as we use the ... of techniques to apply in a particular situation depends on the nature of the datamining task, the nature of the available data, and the skills and preferences of the data miner. Data mining...
... 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 ... discussed, 7 Data Preparation forDataMining (Dorian Pyle), 75 The Data Warehouse Toolkit (Ralph Kimball), 474 data warehousing customer patterns, 5 for decision support, 13 discussed, 4 database ... Business Modeling and Data 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 call-center...
... analyzing data on the information. can provide value. into actionable information using datamining techniques. Identify Transform data 1 2 3 4 5 6 7 8 9 10 Measure the results of the efforts ... of datamining in practice. Figure 2.1 shows the four stages: 1. Identifying the business problem. 2. Miningdata to transform the data into actionable information. 3. Acting on the information. ... the dataminingtechniques discussed in this book are suitable for use in prediction so long as training data is available in the proper form. The 470643 c02.qxd 3/8/04 11:09 AM Page 21of Data...
... 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 ... c04.qxd 3/8/04 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...
... which messages are most appropriate for each one. Even a customer with low scores for every offer has higher scores for some then others. In Mastering DataMining (Wiley, 1999), we describe how ... 11:10 AM 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 ... for other reasons as well. For instance, it is one way of taking several variables and converting them to similar ranges. This can be useful for several datamining techniques, such as clustering...
... in several areas: ■■ Data miners tend to ignore measurement error in raw data. ■■ Data miners assume that there is more than enough data and process-ing power. ■■ Datamining assumes dependency ... make the same classification, although each leaf makes that classificationfor a different reason. For example, in a tree that classifies fruits and vegetables by color, the leaves for apple, ... 11:11 AM Page 159The Lure of Statistics: DataMining Using Familiar Tools 159 statisticians use similar techniques to solve similar problems, the datamining approach differs from the standard...
... Networks 219 Neural Networks for Directed DataMining The previous example illustrates the most common use of neural networks: building a model forclassification or prediction. The steps in this ... 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. ... children variable might be mapped as follows: 0 (for 0 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 easier...
... not appropri-ate for all types of problems. It is not a prediction tool or classification tool like a neural network that takes data in and produces an answer. Many types of data are simply ... 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 ... X. Clearly, they must all be converted to a common scale before distances will make any sense. Unfortunately, in commercial datamining there is usually no common scale available because the...
... calculation for these customers, paying par-ticular attention to the role of censoring. When looking at customer datafor hazard calculations, both the tenure and the censoring flag are needed. For ... the data speak instead of finding a special function to speak for it. Empirical hazard probabilities simply let the historical data determine what is likely to happen, without trying to fit data ... 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...
... Choosing a DataMining Technique The choice of which datamining technique or techniques to apply depends on the particular datamining task to be accomplished and on the data available for analysis. ... to build the datamining team and secure sponsorship for a data mining pilot. The successful efforts crossed corporate boundaries to involve people from both marketing and information technology. ... understood the data, people who understood the datamining techniques, peo-ple who understood the business problem to be addressed, and at least one person with experience applyingdatamining to...