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ASF GitHub Bot commented on FLINK-1807:
---------------------------------------
Github user tillrohrmann commented on a diff in the pull request:
https://github.com/apache/flink/pull/613#discussion_r29837932
--- Diff: flink-staging/flink-ml/src/test/scala/org/apache/flink/ml/optimization/RegularizationITSuite.scala
---
@@ -0,0 +1,54 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.flink.ml.optimization
+
+import org.apache.flink.ml.common.WeightVector
+import org.apache.flink.ml.math.DenseVector
+import org.scalatest.{Matchers, FlatSpec}
+
+import org.apache.flink.api.scala._
+import org.apache.flink.test.util.FlinkTestBase
+
+
+class RegularizationITSuite extends FlatSpec with Matchers with FlinkTestBase {
+
+ behavior of "The regularization type implementations"
+
+ it should "not change the weights when no regularization is used" in {
+
+ val env = ExecutionEnvironment.getExecutionEnvironment
+
+ env.setParallelism(2)
+
+ val regType = new NoRegularization
+
+ val weightVector = new WeightVector(DenseVector(1.0), 1.0)
+ val effectiveStepsize = 1.0
+ val regularizationParameter = 0.0
+ val gradient = DenseVector(0.0)
+
+ regType.takeStep(weightVector.weights, gradient, effectiveStepsize, 0.0)
+
+ weightVector.weights shouldEqual DenseVector(1.0)
+ weightVector.intercept should be (1.0 +- 0.0001)
+
+ }
+
+ // TODO: Unit tests for L1, L2 calculations
--- End diff --
What about those?
> Stochastic gradient descent optimizer for ML library
> ----------------------------------------------------
>
> Key: FLINK-1807
> URL: https://issues.apache.org/jira/browse/FLINK-1807
> Project: Flink
> Issue Type: Improvement
> Components: Machine Learning Library
> Reporter: Till Rohrmann
> Assignee: Theodore Vasiloudis
> Labels: ML
>
> Stochastic gradient descent (SGD) is a widely used optimization technique in different
ML algorithms. Thus, it would be helpful to provide a generalized SGD implementation which
can be instantiated with the respective gradient computation. Such a building block would
make the development of future algorithms easier.
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