lindong28 commented on code in PR #219:
URL: https://github.com/apache/flink-ml/pull/219#discussion_r1139907982
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flink-ml-lib/src/main/java/org/apache/flink/ml/classification/logisticregression/LogisticRegressionModel.java:
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@@ -149,22 +152,14 @@ public Row map(Row dataPoint) {
getRuntimeContext().getBroadcastVariable(broadcastModelKey).get(0);
coefficient = modelData.coefficient;
}
- DenseVector features = ((Vector)
dataPoint.getField(featuresCol)).toDense();
- Row predictionResult = predictOneDataPoint(features, coefficient);
- return Row.join(dataPoint, predictionResult);
- }
- }
+ Vector features = (Vector) dataPoint.getField(featuresCol);
+
+ LogisticRegressionModelServable servable =
+ new LogisticRegressionModelServable(
Review Comment:
Making `LogisticRegressionModelServable(LogisticRegressionModelData) `
protected sounds OK to me.
However, asking developers to identify and forward selected parameters from
model to servable is not very convenient and introduces chances of human error.
It will much more convenient for Flink ML to provide infra that algorithm
developers can use to forward parameters, similar to how the existing
Estimators forward parameters to Model using `ParamUtils.updateExistingParams`.
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