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University of the Cumberlands Wk 6 Data Mining and Association Rule Discussion

 

Introduction to data mining

The genre of data mining aids in extracting and exploring the patterns located in very large sets of data and also engages methods intersecting the subjects of machine learning, database system and statistics.

Association Rule in Data Mining

The concept of association rule is a learning technique carried out to check for various dependencies in the data items so that one can find a predictive relationship and generate profits. The relationship between one data item and another can be interesting for the business serving the consumers. The discovery rule is used here to develop such inter relationship of variables located in databases (Hemmatian,, 2017, p. 1495).

Significance of Association Rule

The association rule is important and is used majorly in machine learning in big data analytics. It is used in the form of market analysis, web use mining or continuous production modules. Such technique is used by commercial trader to find demand for products and as per the pattern actions are taken to attract and certain the consumers.

In commercial business large amount of data is collected in databases every day, Association rule help check the data (Tan, P., Michael, Karpatne & Kumar, (2021). Consumer purchase information for example is stored daily from checkout points and online stores. Managers can analyse data with association rule and develop purchase behaviour prediction for each consumer.

Association Rule Impacts in Advanced Data Interpretation

The association rule is used to interpret advanced data too. It has many advance uses such as medical analysis, protein sequence analysis and market analysis (Poonsirivong & Jittawiriaynukoon, (2018, p. 1). In a medial segment association rule helps make better cure possible for the patients as it can analyze and show probability of an illness from occurring or reoccurring. The association rule also is used in syntheses determination of superficial proteins.

Worldwide such concepts are used to develop better insights for businesses.