Free Data Mining template


Data Mining process introduction, firstly is Cross Industry Standard Process for Data Mining with six phases, then is the five Phases of SEMMA, and lastly, five stages for Knowledge Discovery in Databases (KDD) process. 

Data mining is the computing process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. You can learn more about this concept from Wikipedia. Polls conducted in 2002, 2004, 2007 and 2014 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. Several teams of researchers have published reviews of data mining process models, and Azevedo and Santos conducted a comparison of CRISP-DM and SEMMA in 2008.

The Data Mining Template includes three slides. 

Slide 1, Cross Industry Standard Process for Data Mining.

Cross Industry Standard Process for Data-Mining, commonly known by its acronym CRISP-DM, is a data-mining process model that describes commonly used approaches that data-mining experts use to tackle problems. CRISP-DM breaks the process of data-mining into six major phases, including Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Deployment.

Cross Industry Standard Process for Data Mining with six major phases

Slide 2, Phases of SEMMA.

SEMMA is an acronym that stands for Sample, Explore, Modify, Model, and Assess. It is a list of sequential steps developed by SAS Institute, one of the largest producers of statistics and business intelligence software. It guides the implementation of data-mining applications.

SEMMA process

Slide 3, Knowledge Discovery in Databases (KDD) process.

The knowledge discovery in databases (KDD) process is commonly defined with five stages; they are Selection, Pre-processing, Transformation, Data-mining, and Interpretation/evaluation.

Knowledge Discovery in Databases (KDD) process with five stages

While the term “data mining” itself may have no ethical implications, it is often associated with the mining of information in relation to peoples’ behavior (ethical and otherwise).

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