Icon

Zero-shot text classification and evaluation for Emotion Analysis

Zero-shot text classification for Emotion Analysis

This workflow shows how to use Symanto Brain for zero-shot text classification for the task of emotions classification.

Zero shot classification on the English Unified emotions dataset (Bostan and Klinger, 2018)This workflow shows how to use the Symanto Brain for zero shot text classification, in this case for the task of emotions classification.ReferencesLaura Ana Maria Bostan and Roman Klinger. 2018. An analysis of annotated corpora for emotion classification in text. In Proceedings of the International Conferenceon Computational Linguistics, pages 2104–2119. Association for Computational Linguistics. Dataset freely available under the MIT license. Load and preprocess dataset Dataset statistics Shows the statistical properties of thedataset. Zero-shot classification with Symanto BrainPlease note that the zero-shot task parameters (labels, language, etc.)and the authentication key must be introduced inside the Zero-shotcomponent. Specifically at the Authentication and Zero-shotcomponents, respectively. Evaluate the modelCompute a confusion matrix betweenreal and predicted class values andcalculate the related metrics. Node 9unifiedNode 513Node 514Node 518 DuplicateRow Filter CSV Reader Dataset statisticscomponent Scorer Column Appender Zero Shot component ROC Curve Zero shot classification on the English Unified emotions dataset (Bostan and Klinger, 2018)This workflow shows how to use the Symanto Brain for zero shot text classification, in this case for the task of emotions classification.ReferencesLaura Ana Maria Bostan and Roman Klinger. 2018. An analysis of annotated corpora for emotion classification in text. In Proceedings of the International Conferenceon Computational Linguistics, pages 2104–2119. Association for Computational Linguistics. Dataset freely available under the MIT license. Load and preprocess dataset Dataset statistics Shows the statistical properties of thedataset. Zero-shot classification with Symanto BrainPlease note that the zero-shot task parameters (labels, language, etc.)and the authentication key must be introduced inside the Zero-shotcomponent. Specifically at the Authentication and Zero-shotcomponents, respectively. Evaluate the modelCompute a confusion matrix betweenreal and predicted class values andcalculate the related metrics. Node 9unifiedNode 513Node 514Node 518 DuplicateRow Filter CSV Reader Dataset statisticscomponent Scorer Column Appender Zero Shot component ROC Curve

Nodes

Extensions

Links

Download

To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: mchinea
Created at: 2023-02-17
On NodePit since: 2023-04-27
Last update: 2024-04-28
Created with KNIME version: v4.7.0
Tags: Emotion detectionEmotion analysisEmotions classificationDeep learningMachine learningNLPText classificationZero-shotSymanto

Deploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.

Try NodePit Runner!