Type Mean
Namespace tensorflow.keras.metrics
Parent Reduce
Interfaces IMean
Computes the (weighted) mean of the given values. For example, if values is [1, 3, 5, 7] then the mean is 4.
If the weights were specified as [1, 1, 0, 0] then the mean would be 2. This metric creates two variables, `total` and `count` that are used to
compute the average of `values`. This average is ultimately returned as `mean`
which is an idempotent operation that simply divides `total` by `count`. If `sample_weight` is `None`, weights default to 1.
Use `sample_weight` of 0 to mask values. Usage:
Usage with tf.keras API:
Show Example
m = tf.keras.metrics.Mean() m.update_state([1, 3, 5, 7]) print('Final result: ', m.result().numpy()) # Final result: 4.0
Properties
- activity_regularizer
- activity_regularizer_dyn
- built
- count
- dtype
- dtype_dyn
- dynamic
- dynamic_dyn
- inbound_nodes
- inbound_nodes_dyn
- input
- input_dyn
- input_mask
- input_mask_dyn
- input_shape
- input_shape_dyn
- input_spec
- input_spec_dyn
- losses
- losses_dyn
- metrics
- metrics_dyn
- name
- name_dyn
- name_scope
- name_scope_dyn
- non_trainable_variables
- non_trainable_variables_dyn
- non_trainable_weights
- non_trainable_weights_dyn
- outbound_nodes
- outbound_nodes_dyn
- output
- output_dyn
- output_mask
- output_mask_dyn
- output_shape
- output_shape_dyn
- PythonObject
- reduction
- stateful
- submodules
- submodules_dyn
- supports_masking
- total
- trainable
- trainable_dyn
- trainable_variables
- trainable_variables_dyn
- trainable_weights
- trainable_weights_dyn
- updates
- updates_dyn
- variables
- variables_dyn
- weights
- weights_dyn