shenzgang

How do I deploy my model into production as a predictive service?

Why does the data need to include label columns when using models for prediction? The training model sample contains feature columns and tag columns, but the data that needs to...

I used Titan data to get the model and then load the model to predict, I removed the tag column prediction failure! The prediction data must contain the same number...

Thanks for your reply! There is also the question of how to use the generated model to predict unlabeled test sample data. Are there any examples of using model prediction?

The data set used for model training is labeled column, while the test data is not labeled column. When calling score(), an exception will be thrown

@snabar Do you want to dynamically specify specific feature types? You might try to dynamically convert the type you want using the Row subscript, but there are problems with saving...

@tovbinm There may be some problems here： uid: String = UID[PickListTransformer]) Error message: Cannot resolve symbol PickListTransformer and val realOpFeatures = features.zipWithIndex.map { case (feature, i) if i == id...

@tovbinm,Thank you for your reply!but Maybe there are still some problems！ ``` at ToPickListTransformer class Error:(15, 9) type arguments [org.apache.spark.sql.Row,com.salesforce.op.features.types.PickList] do not conform to class UnaryTransformer's type parameter bounds [I...

First you should set "key.ignore":"false" and then define a transformation. As well as ValueToKey you need ExtractField to convert the key from an object to a plain field: transforms=InsertKey,ExtractId transforms.InsertKey.type=org.apache.kafka.connect.transforms.ValueToKey...