tfp.substrates.numpy.stats.kendalls_tau
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Computes Kendall's Tau for two ordered lists.
tfp.substrates.numpy.stats.kendalls_tau(
y_true, y_pred, name=None
)
Kendall's Tau measures the correlation between ordinal rankings.
The provided values may be of any type that is sortable, with the
argsort indices indicating the true or proposed ordinal sequence.
Args |
|---|
y_true
|
a Tensor of shape [n] containing the true ordinal ranking.
|
y_pred
|
a Tensor of shape [n] containing the predicted ordering of the
same N items.
|
name
|
Optional Python str name for ops created by this method.
Default value: None (i.e., 'kendalls_tau').
|
Returns |
|---|
kendalls_tau
|
Kendall's Tau, the 1945 tau-b formulation that ignores
ordering of ties, as a float32 scalar Tensor.
|
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Last updated 2023-11-21 UTC.
[null,null,["Last updated 2023-11-21 UTC."],[],[],null,["# tfp.substrates.numpy.stats.kendalls_tau\n\n\u003cbr /\u003e\n\n|--------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/probability/blob/v0.23.0/tensorflow_probability/substrates/numpy/stats/kendalls_tau.py#L56-L102) |\n\nComputes Kendall's Tau for two ordered lists.\n\n#### View aliases\n\n\n**Main aliases**\n\n[`tfp.experimental.substrates.numpy.stats.kendalls_tau`](https://www.tensorflow.org/probability/api_docs/python/tfp/substrates/numpy/stats/kendalls_tau)\n\n\u003cbr /\u003e\n\n tfp.substrates.numpy.stats.kendalls_tau(\n y_true, y_pred, name=None\n )\n\nKendall's Tau measures the correlation between ordinal rankings.\nThe provided values may be of any type that is sortable, with the\nargsort indices indicating the true or proposed ordinal sequence.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|----------|----------------------------------------------------------------------------------------------------------|\n| `y_true` | a `Tensor` of shape `[n]` containing the true ordinal ranking. |\n| `y_pred` | a `Tensor` of shape `[n]` containing the predicted ordering of the same N items. |\n| `name` | Optional Python `str` name for ops created by this method. Default value: `None` (i.e., 'kendalls_tau'). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|----------------|--------------------------------------------------------------------------------------------------------|\n| `kendalls_tau` | Kendall's Tau, the 1945 tau-b formulation that ignores ordering of ties, as a `float32` scalar Tensor. |\n\n\u003cbr /\u003e"]]
View source on GitHub