Sentiment Classification with NGrams

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. The two models are then compared via a ROC curve.

Sentiment Classification with NGrams

 

Resources

EXAMPLES Server: 08_Other_Analytics_Types/01_Text_Processing/07_Sentiment_Classification_with_NGrams08_Other_Analytics_Types/01_Text_Processing/07_Sentiment_Classification_with_NGrams*
Download a zip-archive

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* Find more about the Examples Server here.
The link will open the workflow directly in KNIME Analytics Platform (requirements: Windows; KNIME Analytics Platform must be installed with the Installer version 3.2.0 or higher). In other cases, please use the link to a zip-archive or open the provided path manually