train_lstm: Train LSTM model

In adityamangal410/deepSentimentR: Package to Analyze Sentiment Datasets

Description

Train LSTM model using keras on the given dataset

Arguments

data	the sentiment140 train dataset with text for text of the tweet and polarity for polarity.
max_words	Maximum number of words to consider using word frequency measure.
maxlen	Maximum length of a sequence.
embedding_dim	Output dimension of the embedding layer.
epochs	Number of epochs to run the training for.
batch_size	Batch Size for model fitting.
validation_split	Split ratio for validation
lstm_units	Number of units i.e. output dimension of lstm layer.
seed	Seed for shuffling training data.
model_save_path	File path location for saving model.

Value

plot of the training operation showing train vs validation loss and accuracy.

Examples

## Not run: 
  data(sentiment140_train)
  train_lstm(model_save_path = "./train_no_glove_lstm.h5")

## End(Not run)

adityamangal410/deepSentimentR documentation built on June 3, 2019, 6:15 p.m.