train_on_batch: Single gradient update or model evaluation over one batch of...
In dfalbel/keras: R Interface to 'Keras'

Description Usage Arguments Value See Also

Single gradient update or model evaluation over one batch of samples.

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train_on_batch(object, x, y, class_weight = NULL, sample_weight = NULL)

test_on_batch(object, x, y, sample_weight = NULL)

`object`	Keras model object
`x`	input data, as an array or list of arrays (if the model has multiple inputs).
`y`	labels, as an array.
`class_weight`	named list mapping classes to a weight value, used for scaling the loss function (during training only).
`sample_weight`	sample weights, as an array.

Scalar training or test loss (if the model has no metrics) or list of scalars (if the model computes other metrics). The property model$metrics_names will give you the display labels for the scalar outputs.

Other model functions: compile.keras.engine.training.Model(), evaluate.keras.engine.training.Model(), evaluate_generator(), fit.keras.engine.training.Model(), fit_generator(), get_config(), get_layer(), keras_model_sequential(), keras_model(), multi_gpu_model(), pop_layer(), predict.keras.engine.training.Model(), predict_generator(), predict_on_batch(), predict_proba(), summary.keras.engine.training.Model()