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https://issues.apache.org/jira/browse/FLINK-1992?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14550385#comment-14550385
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ASF GitHub Bot commented on FLINK-1992:
---------------------------------------
Github user thvasilo commented on a diff in the pull request:
https://github.com/apache/flink/pull/692#discussion_r30595561
--- Diff:
flink-staging/flink-ml/src/test/scala/org/apache/flink/ml/optimization/GradientDescentITSuite.scala
---
@@ -205,6 +190,61 @@ class GradientDescentITSuite extends FlatSpec with
Matchers with FlinkTestBase {
}
- // TODO: Need more corner cases
+ it should "terminate early if the convergence criterion is reached" in {
+ // TODO(tvas): We need a better way to check the convergence of the
weights.
+ // Ideally we want to have a Breeze-like system, where the optimizers
carry a history and that
+ // can tell us whether we have converged and at which iteration
+
+ val env = ExecutionEnvironment.getExecutionEnvironment
+
+ env.setParallelism(2)
+
+ val sgdEarlyTerminate = GradientDescent()
+ .setConvergenceThreshold(1e2)
+ .setStepsize(1.0)
+ .setIterations(800)
+ .setLossFunction(SquaredLoss())
+ .setRegularizationType(NoRegularization())
+ .setRegularizationParameter(0.0)
+
+ val inputDS = env.fromCollection(data)
+
+ val weightDSEarlyTerminate = sgdEarlyTerminate.optimize(inputDS, None)
+
+ val weightListEarly: Seq[WeightVector] =
weightDSEarlyTerminate.collect()
+
+ weightListEarly.size should equal(1)
+
+ val weightVectorEarly: WeightVector = weightListEarly.head
+ val weightsEarly =
weightVectorEarly.weights.asInstanceOf[DenseVector].data
+ val weight0Early = weightVectorEarly.intercept
+
+ val sgdNoConvergence = GradientDescent()
+ .setStepsize(1.0)
--- End diff --
One solution is for the set*Parameter methods to return this.type instead
of Solver, IterativeSolver etc.
Any objections to using this approach?
> Add convergence criterion to SGD optimizer
> ------------------------------------------
>
> Key: FLINK-1992
> URL: https://issues.apache.org/jira/browse/FLINK-1992
> Project: Flink
> Issue Type: Improvement
> Components: Machine Learning Library
> Reporter: Till Rohrmann
> Assignee: Theodore Vasiloudis
> Labels: ML
>
> Currently, Flink's SGD optimizer runs for a fixed number of iterations. It
> would be good to support a dynamic convergence criterion, too.
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