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Data Mining Project Life Cycle Expand / Collapse
Posted Friday, October 15, 2010 12:42 AM

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The initial post on Data Mining has recieved till date more than 800 hits.

This is another post which will feature the life cycle of any Data Mining Project

Step 1: A mining model is built which consists of a sample data. The sample data is the source data using which the business has to conduct any predictive analytical process.

Step 2: The mining model is then exposed to a training model. The training model is the sort of sample data which will be used to extact patterns from the underlying mining model using the Data Mining Engine.

Step 3: The refined mining model is now exposed to a set of data which is to be predicted. the Data Mining engine will then produce the "Predicted Data" for a relative scenario.

The process of Data Mining is gradual and a continuous learning model. The sole target is to refine the mining model to produce crispier and reliable model.

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Post #1004926
Posted Thursday, December 30, 2010 9:13 AM


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OK, and how do you include "unknown unknowns" into your model. That was the first question, second question would be, what about inovation, like new product or new service, with distinct adwantage over the competition. Like Bill Gates v IBM, Google v Alta Vista and Yahoo.

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