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Statistics can help greatly in this process by helping to answer several important questions about your data: Certainly statistics can do more than answer these questions but for most people today these are the questions that statistics can help answer.
Consider for example that a large part of statistics is concerned with summarizing data, and more often than not, this summarization has to do with counting.
Overall, six broad classes of data mining algorithms are covered.
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This section should help the user to understand the rough differences in the techniques and at least enough information to be dangerous and well armed enough to not be baffled by the vendors of different data mining tools.
The main techniques that we will discuss here are the ones that are used 99.9% of the time on existing business problems.
These two sections have been broken up based on when the data mining technique was developed and when it became technically mature enough to be used for business, especially for aiding in the optimization of customer relationship management systems.
Thus this section contains descriptions of techniques that have classically been used for decades the next section represents techniques that have only been widely used since the early 1980s.
clean data, a well defined target to predict and good validation to avoid overfitting).
And for the most part the techniques are used in the same places for the same types of problems (prediction, classification discovery). Because of the use of computers for closed loop business data storage and generation there now exists large quantities of data that is available to users.
This is certainly more true today than it was when the basic ideas of probability and statistics were being formulated and refined early this century.
Today people have to deal with up to terabytes of data and have to make sense of it and glean the important patterns from it.
However, statistics is probably a much friendlier branch of mathematics because it really can be used every day.Tags: Adult Dating, affair dating, sex dating