Data mining and pattern recognition form the cornerstone of modern data science by enabling the extraction of meaningful information from vast and complex data sets.

Data analysis and data mining tools use quantitative analysis, cluster analysis, pattern recognition, correlation discovery, and associations to analyze data with little or no IT intervention.

Association is one of the simplest data mining techniques users can leverage – it’s one of the first data mining techniques users can leverage once they’ve practiced their pattern tracking.

Of the seven patterns of AI that represent the ways in which AI is being implemented, one of the most common is the recognition pattern.

Data mining has been in widespread use for the better part of this decade for everything from marketing to to bitcoin. The initial idea was that keywords, phrases, and even images and shapes can be ...

Cluster detection: one type of pattern recognition that is particularly useful is recognizing distinct clusters or sub-categories within the data.

Machine learning enables pattern recognition, which can assist public safety officials in easily identifying crime patterns. The NYPD uses a machine learning-based application called Patternizer. Read ...

This article discusses statistical and data mining methods used in credit scoring, highlighting their applications and effectiveness in evaluating credit risk.