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Lets return to the adult data set for an example of how to calculate the J -measure. We applied Clementines GRI algorithm to the categorical variables in the data set, again specifying minimum support of 10% and minimum confidence of 75%, and setting the rule table maximum size to 30. The results are shown in [...]

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EPILOGUE
Weve Only Just Begun An Invitation to Data Mining Methods and Models
I hope you have enjoyed Discovering Knowledge in Data: An Introduction to Data Mining, and that our experience together has whetted your appetite for learning more about this unique and powerful field of study. In fact, it is true that we have only just [...]

In Olympic figure skating, the best-performing skater is not selected by a single judge alone. Instead, a suite of several judges is called upon to select the best skater from among all the candidate skaters. Similarly in model selection, whenever possible, the analyst should not depend solely on a single data mining method. Instead, he [...]

In Chapter 1 the graphic representing the CRISPDMstandard process for data mining contained a feedback loop between the model building and evaluation phases. In Chapter 5 (Figure 5.1) we presented a methodology for supervised modeling. Where do the methods for model evaluation from Chapter 11 fit into these processes?

Lift charts are often presented in their cumulative form, where they are denoted as cumulative lift charts, or gains charts. The gains chart associated with the lift chart in Figure 11.5 is presented in Figure 11.6. The diagonal on the gains chart is analogous to the horizontal axis at lift = 1 on the lift [...]

Lift is a function of sample size, which is why we had to specify that the lift of 3.17 for model 1 was measured at n = 4824 records. When calculating lift, the software will first sort the records by the probability of being classified positive. The lift is then calculated for every sample size [...]

Lift charts and gains charts are graphical evaluative methods for assessing and comparing the usefulness of classification models. Lift is a concept, originally from the marketing field, which seeks to compare the response rates with and without using the classification model.We shall explore these concepts by continuing our examination of the C5.0 models for classifying [...]