By Shirley Coleman, Andrea Ahlemeyer-Stubbe
Info mining is easily on its technique to changing into a famous self-discipline within the overlapping components of IT, records, laptop studying, and AI. useful facts Mining for enterprise provides a undemanding method of info mining equipment, masking the common makes use of to which it truly is utilized. The technique is complemented by means of case reviews to create a flexible reference e-book, permitting readers to seem for particular tools in addition to for particular functions. The ebook is formatted to permit statisticians, laptop scientists, and economists to
cross-reference from a selected program or technique to sectors of curiosity.
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Extra resources for A Practical Guide to Data Mining for Business and Industry
If we are dealing with smallish amounts of data (up to 10 000 cases), then we may prefer to work with the whole dataset. If we are dealing with larger d atasets, we may choose to work with a subset for ease of manipulation. If the analysis is carried out on a sample, the implication is that the results will be representative of the whole population. In other words, the results of the analysis on the sample can be generalised to be relevant for the whole population. The sample therefore has to be good, by which we mean that it has to be representative and unbiased.
D = Data which is facts without context I = Information which is facts with some context and perspective K = Knowledge which is information used to detect and understand patterns in the data W = Wisdom which is knowledge and happens when you understand why the patterns are occurring It may seem unusual to write about knowledge management and data theory in an applied book for data mining, but this viewpoint may help to understand how knowledge that may or may not be part of the data itself can and should be included in data preparation.
28 A Practical Guide to Data Mining for Business and Industry, First Edition. Andrea Ahlemeyer-Stubbe and Shirley Coleman. © 2014 John Wiley & Sons, Ltd. Published 2014 by John Wiley & Sons, Ltd. 1 Types of Data Mining Questions Data mining covers a wide range of activities. It seeks to provide the answer to questions such as these: ●● ●● ●● What is contained in the data? What kinds of patterns can be discerned from the maze of data? How can all these data be used for future benefit? 1 Population and Sample In data mining, datasets can be enormous – there may be millions of cases.