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[P] Refit existing Spark ML PipelineModel with new data

Hi!

I’d like to refit an alerady existing PipeLineModel in my project from microbatch to microbatch.

I curently use a DecisionTreeRegressor. I load back the previusly used PipelineModel, set it’s stages to a pipeline and use that pipeline to refit with new data, but as I can understand my solution only saves the latest model.

I enclose my github repo/model for the easier understanding.

Does Spark Structured Streaming capable of streaming learning? Is it possible to refit my already fitted model with new data?

Do I have to use the RDD based Spark Streaming with StreamingLinearRegressionWithSGD?

submitted by /u/Hakuhun
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.