11.4 Identifying Problems with a Data Survey

11.4 Identifying Problems with a Data Survey

There is fundamentally one reason and three problems that can reduce or prevent mining tools from identifying a good relationship between input and output data sets. They are

Reason: The data set simply does not enfold sufficient information to define the relationship between input and output with the accuracy required.


	?	Problem 1: The relationship between input and output is very complex.


	?	Problem 2: Part(s) of the input/output relationship are not well defined by the available data.


	?	Problem 3: High variance or noise obscures the underlying relationship between input and output.

Turning first to the reason: The data set simply does not contain sufficient information to define the relationship to the accuracy required. This is not essentially a problem with the data sets, input and output. It may be a problem for the miner, but if sufficient data exists to form a multivariably representative sample, there is nothing that can be done to ?fix? such data. If the data on hand simply does not define the relationship as needed, the only possible answer is to get other data that does. A miner always needs to keep clearly in mind that the solution to a problem lies in the problem domain, not in the data. In other words, a business may need more profit, more customers, less overhead, or some other business solution. The business does not need a better model, except as a means to an end. There...

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Data Preparation for Data Mining

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11.4 Identifying Problems with a Data Survey

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