Vectors in Data Mining and Pattern Recognition

Data Mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information. [1]

Pattern recognition is often considered to be a technique separate from data
mining, but its definition is related: “the act of taking in raw data and making
an action based on the ‘category’ of the pattern. [2]

There are numerous application areas for data mining, ranging from e-business
to bioinformatics, from scientific applications such as the classification of volcanos on Venus to information retrieval and Internet search engines.

Linear algebra and data analysis are basic ingredients in many data mining techniques and to treat data by mathematical methods, it needs structures such as matrix and vectors to analyze and predict patterns.

tableau-visualization-using-sap-business-warehouse

image source: http://data-informed.com/wp-content/uploads/2012/05/Tableau-visualization-using-SAP-Business-Warehouse.jpg

silverlight-executive-dashboard

image source: http://www.dashboardinsight.com/CMS/3b3fc941-bad0-427c-9015-b6acf58ea8a1/Silverlight-executive-dashboard.png

References:
[1] Data Mining: What is Data Mining? (n.d.). Retrieved January 29, 2017, from http://www.anderson.ucla.edu/faculty/jason.frand/teacher/technologies/palace/datamining.htm

[2] Vectors and Matrices in Data Mining and Pattern Recognition, from https://www.siam.org/books/fa04/FA04chapter1.pdf

Advertisements