LostTech.TensorFlow : API Documentation

Type SquaredHinge

Namespace tensorflow.keras.metrics

Parent MeanMetricWrapper

Interfaces ISquaredHinge

Computes the squared hinge metric between `y_true` and `y_pred`.

`y_true` values are expected to be -1 or 1. If binary (0 or 1) labels are provided we will convert them to -1 or 1.

For example, if `y_true` is [-1., 1., 1.], and `y_pred` is [0.6, -0.7, -0.5] the squared hinge metric value is 2.6.

Usage: Usage with tf.keras API:
Show Example
m = tf.keras.metrics.SquaredHinge()
            m.update_state([-1., 1., 1.], [0.6, -0.7, -0.5]) 

# result = max(0, 1-y_true * y_pred) = [1.6^2 + 1.7^2 + 1.5^2] / 3

print('Final result: ', m.result().numpy()) # Final result: 2.6


Public properties

PythonFunctionContainer activity_regularizer get; set;

object activity_regularizer_dyn get; set;

bool built get; set;

object count get; set;

object dtype get;

object dtype_dyn get;

bool dynamic get;

object dynamic_dyn get;

IList<Node> inbound_nodes get;

object inbound_nodes_dyn get;

IList<object> input get;

object input_dyn get;

object input_mask get;

object input_mask_dyn get;

IList<object> input_shape get;

object input_shape_dyn get;

object input_spec get; set;

object input_spec_dyn get; set;

IList<object> losses get;

object losses_dyn get;

IList<object> metrics get;

object metrics_dyn get;

object name get;

object name_dyn get;

object name_scope get;

object name_scope_dyn get;

IList<object> non_trainable_variables get;

object non_trainable_variables_dyn get;

IList<object> non_trainable_weights get;

object non_trainable_weights_dyn get;

IList<object> outbound_nodes get;

object outbound_nodes_dyn get;

IList<object> output get;

object output_dyn get;

object output_mask get;

object output_mask_dyn get;

object output_shape get;

object output_shape_dyn get;

object PythonObject get;

string reduction get; set;

bool stateful get; set;

ValueTuple<object> submodules get;

object submodules_dyn get;

bool supports_masking get; set;

object total get; set;

bool trainable get; set;

object trainable_dyn get; set;

object trainable_variables get;

object trainable_variables_dyn get;

IList<object> trainable_weights get;

object trainable_weights_dyn get;

IList<object> updates get;

object updates_dyn get;

object variables get;

object variables_dyn get;

IList<object> weights get;

object weights_dyn get;