asreview.models.classifiers.NN2LayerClassifier

class asreview.models.classifiers.NN2LayerClassifier(dense_width=128, optimizer='rmsprop', learn_rate=1.0, regularization=0.01, verbose=0, epochs=35, batch_size=32, shuffle=False, class_weight=30.0)[source]

Fully connected neural network (2 hidden layers) classifier (nn-2-layer).

Neural network with two hidden, dense layers of the same size.

Recommended feature extraction model is asreview.models.feature_extraction.Doc2Vec.

Note

This model requires tensorflow to be installed. Use pip install tensorflow or install all optional ASReview dependencies with pip install asreview[all]

Warning

Might crash on some systems with limited memory in combination with asreview.models.feature_extraction.Tfidf.

Parameters

  • dense_width (int) – Size of the dense layers.

  • optimizer (str) – Name of the Keras optimizer.

  • learn_rate (float) – Learning rate multiplier of the default learning rate.

  • regularization (float) – Strength of the regularization on the weights and biases.

  • verbose (int) – Verbosity of the model mirroring the values for Keras.

  • epochs (int) – Number of epochs to train the neural network.

  • batch_size (int) – Batch size used for the neural network.

  • shuffle (bool) – Whether to shuffle the training data prior to training.

  • class_weight (float) – Class weights for inclusions (1’s).

Attributes

default_param

Get the default parameters of the model.

label

name

param

Get the (assigned) parameters of the model.

Methods

fit(X, y)

Fit the model to the data.

full_hyper_space()

Get a hyperparameter space to use with hyperopt.

hyper_space()

predict_proba(X)

Get the inclusion probability for each sample.