How to Use TF-IDF for Classification & Document Separation

Both Grooper's Natural Language Processing capabilities through TF-IDF machine learning and ESP Auto Document Classification and Separation solve problems previously thought impossible in the world of document processing.

tf-idf classification The cost and effort of organizing and maintaining a clean data set from unstructured documents has been seen as too high in the past. Grooper gives you the tools to make this an efficient reality.

This presentation will walk you though the proper approach using Grooper and an overview of TF-IDF classification and why it is a powerful algorithm. This is a presentation on theory and is a great primer for creating critical understanding before working in Grooper.

Documents Discussed for TF-IDF classification:

Oil and gas lease packets
Contracts
Royalty assignments
Letters
Email
Invoices
Mineral ownership reports

Grooper features:

N-Grams
Stop words
Porter-stemming
Named entity tokens
Field labels
Sequencing hints

Watch our Video Demo and Learn more About TF-IDF Classification!

Speakers

Dylan Greenwood

Dylan GreenwoodTraining and Curriculum Specialist

Watch Video On-Demand

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