Icon

Sentiment_​Deep_​Learning

Sentiment Analysis

This workflow shows how to train a simple neural network for text classification, in this case sentiment analysis. The used network learns a 128 dimensional word embedding followed by an LSTM.

Define Network Reading and Preprocessing Training and Predicting Evaluation Apply DictionaryReadDictionary.tableimdb.tableShape: max number of words per documentsInput: # word in dictionary+2128 unitsActivation function:sigmoidtrain for 3 epochswith Adamprobability topredictionpredict testdata Strings To Document Dictionary Replacer Partitioning Table Reader Table Reader Keras Input Layer Reduce Dictionary Truncate Keras EmbeddingLayer Keras LSTM Layer Keras Dense Layer Keras NetworkLearner Rule Engine Scorer (JavaScript) Keras NetworkExecutor Zero Pad Number To String Define Network Reading and Preprocessing Training and Predicting Evaluation Apply DictionaryReadDictionary.tableimdb.tableShape: max number of words per documentsInput: # word in dictionary+2128 unitsActivation function:sigmoidtrain for 3 epochswith Adamprobability topredictionpredict testdata Strings To Document Dictionary Replacer Partitioning Table Reader Table Reader Keras Input Layer Reduce Dictionary Truncate Keras EmbeddingLayer Keras LSTM Layer Keras Dense Layer Keras NetworkLearner Rule Engine Scorer (JavaScript) Keras NetworkExecutor Zero Pad Number To String

Nodes

Extensions

Links