weibozhao commented on a change in pull request #24:
URL: https://github.com/apache/flink-ml/pull/24#discussion_r755676909
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File path:
flink-ml-lib/src/main/java/org/apache/flink/ml/classification/knn/KnnParams.java
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@@ -0,0 +1,32 @@
+package org.apache.flink.ml.classification.knn;
+
+import org.apache.flink.ml.common.param.HasFeatureColsDefaultAsNull;
+import org.apache.flink.ml.common.param.HasLabelCol;
+import org.apache.flink.ml.common.param.HasPredictionCol;
+import org.apache.flink.ml.common.param.HasVectorColDefaultAsNull;
+import org.apache.flink.ml.param.IntParam;
+import org.apache.flink.ml.param.Param;
+import org.apache.flink.ml.param.ParamValidators;
+import org.apache.flink.ml.param.WithParams;
+
+/** knn fit parameters. */
+public interface KnnParams<T>
+ extends WithParams<T>,
+ HasVectorColDefaultAsNull<T>,
+ HasLabelCol<T>,
+ HasFeatureColsDefaultAsNull<T>,
+ HasPredictionCol<T> {
+ /**
+ * @cn-name topK
+ * @cn topK
+ */
+ Param<Integer> K = new IntParam("k", "k", 10, ParamValidators.gt(0));
+
+ default Integer getK() {
Review comment:
K can be get in tow parttern: getK() or params.get(KnnParams.K)
algorithm's implementation is no problem. I just use the second pattern,
maybe I need change the patten later.
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