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https://issues.apache.org/jira/browse/FLINK-1933?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14518967#comment-14518967
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ASF GitHub Bot commented on FLINK-1933:
---------------------------------------
Github user tillrohrmann commented on a diff in the pull request:
https://github.com/apache/flink/pull/629#discussion_r29318238
--- Diff:
flink-staging/flink-ml/src/main/scala/org/apache/flink/ml/common/distance/DistanceMeasure.scala
---
@@ -0,0 +1,37 @@
+/*
+ * 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.common.distance
+
+import org.apache.flink.ml.math.Vector
+
+/** DistanceMeasure interface is used for object which determine distance
between two points.
--- End diff --
typo: determines
> Add distance measure interface and basic implementation to machine learning
> library
> -----------------------------------------------------------------------------------
>
> Key: FLINK-1933
> URL: https://issues.apache.org/jira/browse/FLINK-1933
> Project: Flink
> Issue Type: New Feature
> Components: Machine Learning Library
> Reporter: Chiwan Park
> Assignee: Chiwan Park
> Labels: ML
>
> Add distance measure interface to calculate distance between two vectors and
> some implementations of the interface. In FLINK-1745, [~till.rohrmann]
> suggests a interface following:
> {code}
> trait DistanceMeasure {
> def distance(a: Vector, b: Vector): Double
> }
> {code}
> I think that following list of implementation is sufficient to provide first
> to ML library users.
> * Manhattan distance [1]
> * Cosine distance [2]
> * Euclidean distance (and Squared) [3]
> * Tanimoto distance [4]
> * Minkowski distance [5]
> * Chebyshev distance [6]
> [1]: http://en.wikipedia.org/wiki/Taxicab_geometry
> [2]: http://en.wikipedia.org/wiki/Cosine_similarity
> [3]: http://en.wikipedia.org/wiki/Euclidean_distance
> [4]:
> http://en.wikipedia.org/wiki/Jaccard_index#Tanimoto_coefficient_.28extended_Jaccard_coefficient.29
> [5]: http://en.wikipedia.org/wiki/Minkowski_distance
> [6]: http://en.wikipedia.org/wiki/Chebyshev_distance
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