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| author |  A. Unique TensorFlower <gardener@tensorflow.org> | 2018-03-21 11:01:54 -0700 |
|---|---|---|
| committer | TensorFlower Gardener <gardener@tensorflow.org> | 2018-03-21 11:04:22 -0700 |
| commit | 53f823c1273c7670fb5c337ae7ac2e9647a1fa4f (patch) | |
| tree | 347821643532461d9279168504ab40a3763732bf /tensorflow/contrib/tensor_forest | |
| parent | d7cb36a6876e02540c13f31f468a84f54c8591d4 (diff) | |
Update the doc to reflect the change of replacing std::clock with random::New64() as random number generator seed.
PiperOrigin-RevId: 189934377
Diffstat (limited to 'tensorflow/contrib/tensor_forest')
| -rw-r--r-- | tensorflow/contrib/tensor_forest/README.md | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/tensorflow/contrib/tensor_forest/README.md b/tensorflow/contrib/tensor_forest/README.md index 8b24430c71..9e1491ea66 100644 --- a/tensorflow/contrib/tensor_forest/README.md +++ b/tensorflow/contrib/tensor_forest/README.md @@ -116,7 +116,7 @@ a different `feature_bagging_fraction * num_features` sized subset of the input features. Defaults to 1.0 (no feature bagging). * `base_random_seed`. By default (`base_random_seed = 0`), the random number -generator for each tree is seeded by the current time (in microseconds) when +generator for each tree is seeded by a 64-bit random value when each tree is first created. Using a non-zero value causes tree training to be deterministic, in that the i-th tree's random number generator is seeded with the value `base_random_seed + i`. |