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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