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Deploying Sentiment Predictor

Deploying a Sentiment Analysis Predictive Model - Supervised Machine Learning
1. Collect and process twitter data. 2. Prepare and classify new data. 3. Visualize data Deploying a Sentiment Analysis Predictive Model - Supervised Machine Learning Common steps(e.g., lower case,stop wors, etc.)Convert strings toto documentsRight click->Configure->Enter yourTwitter API Credentialsand search queryKaggle VectorSpace (Predictors)RF Modeladd back predicted sentimentNode 1294 String Emoji Filter Enrichment andPreprocessing BoW andVector Space Strings To Document Tweet Extraction DocumentVector Applier Model Reader Model Reader Document DataExtractor Visualization Column Filter Joiner (deprecated) Random ForestPredictor 1. Collect and process twitter data. 2. Prepare and classify new data. 3. Visualize data Deploying a Sentiment Analysis Predictive Model - Supervised Machine Learning Common steps(e.g., lower case,stop wors, etc.)Convert strings toto documentsRight click->Configure->Enter yourTwitter API Credentialsand search queryKaggle VectorSpace (Predictors)RF Modeladd back predicted sentimentNode 1294 String Emoji Filter Enrichment andPreprocessing BoW andVector Space Strings To Document Tweet Extraction DocumentVector Applier Model Reader Model Reader Document DataExtractor Visualization Column Filter Joiner (deprecated) Random ForestPredictor

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

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Created by: fvill
Created at: 2021-04-12
On NodePit since: 2022-11-04
Last update: 2024-04-28
Created with KNIME version: v4.6.3
Tags: sentiment analysissentimentmachine learningSVMdeploymentMarketing Analytics

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