RNN model predicting only one class?

问题

I am trying to use GloVe embeddings to train a rnn model based on this article. I have a labeled data: text(tweets) on one column, labels on another (hate, offensive or neither). However the model seems to predict only one class in the result.

This is the LSTM model:

model = Sequential()
hidden_layer = 3
gru_node = 32

# model embedding matrix here....

for i in range(0,hidden_layer):
    model.add(GRU(gru_node,return_sequences=True, recurrent_dropout=0.2))
    model.add(Dropout(dropout))
model.add(GRU(gru_node, recurrent_dropout=0.2))
model.add(Dropout(dropout))
model.add(Dense(64, activation='softmax'))
model.add(Dense(nclasses, activation='softmax'))
start=time.time()
model.compile(loss='sparse_categorical_crossentropy',optimizer='adam',metrics=['accuracy'])

fitting the model:

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2, random_state = 1)
X_train_Glove,X_test_Glove, word_index, embeddings_index = loadData_Tokenizer(X_train, X_test)

model_RNN = Build_Model_RNN_Text(word_index,embeddings_index, 20)    
model_RNN.fit(X_train_Glove,y_train,
                            validation_data=(X_test_Glove, y_test),
                            epochs=4,
                            batch_size=128,
                            verbose=2)
y_preds = model_RNN.predict_classes(X_test_Glove)
print(metrics.classification_report(y_test, y_preds))

Results:

classification report

Confusion matrix

Am I missing something here?

Update: this is what the distribution looks like

and the model summary, more or less

回答1:

How the distribution of your data looks like? The first suggestion is to stratify train/test split (here is the link for the documentation).

The second question is how much data do you have in comparison with the complexity of the model? Maybe, your model is so complex, that just do overfitting. You can use the command model.summary() to see the number of trainable parameters.

来源：https://stackoverflow.com/questions/57748144/rnn-model-predicting-only-one-class

标签

python

machine-learning

keras

lstm

recurrent-neural-network