In this SAS blog, Kirk Swilley and Tom Sabo showcase how given minimal structured data, they leveraged text analytics capabilities to identify patterns in narrative data that could be assessed in intuitive ways. While police departments have additional metadata related to these narrative incidents, it is possible that such metadata only allows for a primary offense, such as a drug abuse incident, while there are indications in the narratives of a secondary issue, such as human trafficking risk. Additionally, similar methods could be leveraged on textual or transcribed tips and other textual data sources of investigation to help filter, classify, and route these leads appropriately for quick action.
Click to read this informative blog.
Use this tutorial as a handy guide to weigh the pros and cons of these commonly used machine learning algorithms.
Find more tutorials on the SAS Users YouTube channel.
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