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Train an LSTM for Sentiment Analysis

This workflow shows how to train an LSTM neural network for text classification based on the example of sentiment analysis.

Define Network Training and Predicting Evaluation Reading and Preprocessing Deployment Train an LSTM Model for Sentiment AnalysisThis workflow shows how to train an LSTM neural network for text classification based on the example of sentiment analysis. Shape: maxsequence lengthInput: # words indictionary + 1128 unitsActivation function:sigmoid1 unitTrain thenetwork Probability to predictionPredicton test dataSave trained modelTraining dataTest data128 unitsKeras Input Layer Keras EmbeddingLayer Keras Dense Layer Keras NetworkLearner Rule Engine Keras NetworkExecutor Scorer Keras NetworkWriter Preprocesstraining set Preprocess test set Table Reader Table Reader Keras LSTM Layer Define Network Training and Predicting Evaluation Reading and Preprocessing Deployment Train an LSTM Model for Sentiment AnalysisThis workflow shows how to train an LSTM neural network for text classification based on the example of sentiment analysis. Shape: maxsequence lengthInput: # words indictionary + 1128 unitsActivation function:sigmoid1 unitTrain thenetwork Probability to predictionPredicton test dataSave trained modelTraining dataTest data128 unitsKeras Input Layer Keras EmbeddingLayer Keras Dense Layer Keras NetworkLearner Rule Engine Keras NetworkExecutor Scorer Keras NetworkWriter Preprocesstraining set Preprocess test set Table Reader Table Reader Keras LSTM Layer

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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: kathrinmelcher
Created at: 2018-06-20
On NodePit since: 2022-12-13
Last update: 2024-04-28
Created with KNIME version: v4.7.0
Tags: deep learningkerastext classificationclassificationlstmembeddingtext analysissequence analysissentiment analysissequence classificationneural networktext processingeducation

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