Sentiment Analysis (Classification) of Documents with NGram Features
This workflow shows how to import text from a csv file, convert it to documents, preprocess the documents and transform them into numerical document vectors consisting of single word and 2-gram features.
Finally two predictive models are trained on the vectors to predict the sentiment class of the documents.
URL: Sentiment Analysis with N-Grams http://www.knime.org/blog/sentiment-analysis-with-n-grams
URL: Slides KNIME Analytics Platform Text Mining https://www.knime.com/form/material-download-registration
To use this workflow in KNIME, download it from the below URL and open it in KNIME:
Download WorkflowDeploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.
Try NodePit Runner!Do you have feedback, questions, comments about NodePit, want to support this platform, or want your own nodes or workflows listed here as well? Do you think, the search results could be improved or something is missing? Then please get in touch! Alternatively, you can send us an email to mail@nodepit.com, follow @NodePit on Twitter or botsin.space/@nodepit on Mastodon.
Please note that this is only about NodePit. We do not provide general support for KNIME — please use the KNIME forums instead.