H2O MOJO Predictor(Autoencoder/Dimension Reduction) nodes usage


I am having a problem using Spark H2O/H2O nodes: Predictor(Autoencoder) and Predictor(Dimension Reduction). I have warnings regarding to the MOJO category which must be DimReduction or AutoEncoder. I uploaded the modified workflow example: “kn_example_h2o_sparkling_water.knwf” from the site. The same problem is when I am using H2O k-Means node instead of H2O Random Forest Learner node.

And I have another question: how can I activate the Sparkling Water Flow UI? I tried to set the “spark.ext.h2o.node.enable.web” key TRUE for the Create H2O Sparkling Water Context node on another workflow on a Linux OS and I have this error: “\n\nERROR MESSAGE:\n\nResource/flow/index.html not found\n\n”. I uploaded the image with this error.

Thank you,

kn_example_h2o_sparkling_water_autoencoder.knwf (110.4 KB)

Thank you for using my example with H2O.ai and Spark. You will have to connect the MOJO File (Reader) to a compatible model from H2O. At the moment they connect to a classification model.

As far as I can see MOJOs for Dimension reduction are not yet represented with individual KNIME/H2O nodes. It might be possible to import such model from R or Python implementations of H2O. I would have to investigate.

It should be possible to build a wrapper for KNIME like I demonstrated for H2O’s AutoML.

Regarding your other question. If you check the context of the local big data node with right click it will provide you with a link. There is also a tab with Sparkling Water information. But unfortunately I was not immediately able to open the GUI.


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