By Dorian Pyle
I've got loads of adventure getting ready info for research. i used to be trying to find a e-book that may upload to my realizing of and increase my association for information instruction. this isn't that publication. At most sensible, the ebook offers perception into the kinds of concerns confronted in getting ready info and emphasizes the price of such. instead of criticize, I desire to foreworn those that have already practiced at a a little rigorous point (more than 5 semesters of statistics/data mining) that this would now not be what you're looking.
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Extra info for Data Preparation for Data Mining (The Morgan Kaufmann Series in Data Management Systems)
Sample text
The first was added when pattern of use information became available. Many credit card issuers feel a strong preference toward customers who are not “convenience users,” those who pay the balance in full when requested and, thus, never generate revenue for the issuer in the form of interest payments. Another increase in the quality of the target potential customers resulted—those who would not only respond and be approved, but also would be profitable for the card issuer. Eventually, default and fraud were modeled and added into the selection process.
The cost of living changes, as does the unemployment level—driven (we say) by the economy and marketplace. ” The features of objects captured as data form a reflection of this great system of the world. If the reflection is accurate, the features themselves, to a greater or lesser degree, represent that system. It is in this sense that data is said to represent or, sometimes, to form a system. 2 Capturing Measurements For the data miner, objects actually consist of measurements of features. It is the groups of features that are taken as the defining characteristics of the objects, and actual instance measurements of the values of those features are considered to represent instances of the object.
Several variables are measured. Each measurement is, of course, subject to the point distortion, or error, described previously. 3 represents such a single measurement. The central point of each circle represents the idealized point value, and the surrounding circle represents the unavoidable accompanying fuzz or error. Whatever the value of the actual measurement, it must be thought of as being somewhere in this fuzzy area, near to the idealized point value. 3 Taking several point measurement values with uncertainty due to error outlines a measurement curve surrounded by an error band.