evaluate.keras.engine.training.Model {keras} | R Documentation |
Evaluate a Keras model
## S3 method for class 'keras.engine.training.Model' evaluate(object, x = NULL, y = NULL, batch_size = NULL, verbose = 1, sample_weight = NULL, steps = NULL, ...)
object |
Model object to evaluate |
x |
Vector, matrix, or array of test data (or list if the model has
multiple inputs). If all inputs in the model are named, you can also pass a
list mapping input names to data. |
y |
Vector, matrix, or array of target (label) data (or list if the model has
multiple outputs). If all outputs in the model are named, you can also pass
a list mapping output names to data. |
batch_size |
Integer or |
verbose |
Verbosity mode (0 = silent, 1 = progress bar, 2 = one line per epoch). |
sample_weight |
Optional array of the same length as x, containing
weights to apply to the model's loss for each sample. In the case of
temporal data, you can pass a 2D array with shape (samples,
sequence_length), to apply a different weight to every timestep of every
sample. In this case you should make sure to specify
|
steps |
Total number of steps (batches of samples) before declaring the
evaluation round finished. Ignored with the default value of |
... |
Unused |
Named list of model test loss (or losses for models with multiple outputs) and model metrics.
Other model functions: compile.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
,
train_on_batch