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Posted to commits@flink.apache.org by tr...@apache.org on 2017/06/02 16:57:44 UTC
flink git commit: [FLINK-6840] [ml] Correct documentation for
multiple linear regression
Repository: flink
Updated Branches:
refs/heads/master 94ade3de9 -> 121482b88
[FLINK-6840] [ml] Correct documentation for multiple linear regression
Project: http://git-wip-us.apache.org/repos/asf/flink/repo
Commit: http://git-wip-us.apache.org/repos/asf/flink/commit/121482b8
Tree: http://git-wip-us.apache.org/repos/asf/flink/tree/121482b8
Diff: http://git-wip-us.apache.org/repos/asf/flink/diff/121482b8
Branch: refs/heads/master
Commit: 121482b88baff1385260691276e8bc6b28756ed5
Parents: 94ade3d
Author: Till Rohrmann <tr...@apache.org>
Authored: Fri Jun 2 18:57:04 2017 +0200
Committer: Till Rohrmann <tr...@apache.org>
Committed: Fri Jun 2 18:57:04 2017 +0200
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docs/dev/libs/ml/multiple_linear_regression.md | 10 +---------
1 file changed, 1 insertion(+), 9 deletions(-)
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http://git-wip-us.apache.org/repos/asf/flink/blob/121482b8/docs/dev/libs/ml/multiple_linear_regression.md
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diff --git a/docs/dev/libs/ml/multiple_linear_regression.md b/docs/dev/libs/ml/multiple_linear_regression.md
index 95ee85f..a5737eb 100644
--- a/docs/dev/libs/ml/multiple_linear_regression.md
+++ b/docs/dev/libs/ml/multiple_linear_regression.md
@@ -75,15 +75,7 @@ MultipleLinearRegression is trained on a set of `LabeledVector`:
MultipleLinearRegression predicts for all subtypes of `Vector` the corresponding regression value:
-* `predict[T <: Vector]: DataSet[T] => DataSet[LabeledVector]`
-
-If we call predict with a `DataSet[LabeledVector]`, we make a prediction on the regression value
-for each example, and return a `DataSet[(Double, Double)]`. In each tuple the first element
-is the true value, as was provided from the input `DataSet[LabeledVector]` and the second element
-is the predicted value. You can then use these `(truth, prediction)` tuples to evaluate
-the algorithm's performance.
-
-* `predict: DataSet[LabeledVector] => DataSet[(Double, Double)]`
+* `predict[T <: Vector]: DataSet[T] => DataSet[(T, Double)]`
## Parameters