Data Mining - Process

Process

The Knowledge Discovery in Databases (KDD) process is commonly defined with the stages:

(1) Selection
(2) Pre-processing
(3) Transformation
(4) Data Mining
(5) Interpretation/Evaluation.

It exists, however, in many variations on this theme, such as the Cross Industry Standard Process for Data Mining (CRISP-DM) which defines six phases:

(1) Business Understanding
(2) Data Understanding
(3) Data Preparation
(4) Modeling
(5) Evaluation
(6) Deployment

or a simplified process such as (1) pre-processing, (2) data mining, and (3) results validation.

Polls conducted in 2002, 2004, and 2007 show that the CRISP-DM methodology is the leading methodology used by data miners. The only other data mining standard named in these polls was SEMMA. However, 3-4 times as many people reported using CRISP-DM. Azevedo and Santos conducted a comparison of CRISP-DM and SEMMA in 2008.

Read more about this topic:  Data Mining

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