[SW-2029] Add H2O GLRM to Algo API #2224
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| JObject(obj) <- ast | ||
| JField("model_summary", JObject(modelSummary)) <- obj | ||
| JField("columns", JArray(columns)) <- modelSummary | ||
| ("final_objective_value", index) <- columns.arr.map(getColumnName).zipWithIndex |
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@wendycwong I'm extracting the metric from model_summary on MOJO model. The name of the value is final_objective_value. Is this the value that we try to minimize during the model training?
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| algo = getPreconfiguredAlgorithm() | ||
| algo.setLossByCol(["absolute", "huber"]) | ||
| algo.setLossByColNames(["Murder", "Rape"]) |
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I've replace loss_by_col_idx with lossByColNames which reference column by their names. Column indices wouldn't work well in SW. I also considered to merge lossByCol and lossByColNames into one map/dictionary parameter, but I didn't that since lossByCol can be used in gridSearch according to the documentation.
ml/src/main/scala/ai/h2o/sparkling/ml/algos/H2OGridSearch.scala
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ml/src/main/scala/ai/h2o/sparkling/ml/algos/H2OGridSearch.scala
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| algo = getPreconfiguredAlgorithm() | ||
| algo.setLossByCol(["absolute", "huber"]) | ||
| algo.setLossByColNames(["Murder", "Rape"]) |
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Also just realized that it might be hard to obtain the reduced frame if we do not explicitly set the responseName because H2O creates the name as What do you think of generating some default name on SW side and mentioning that in docs? |
Is a user able to get
We could generate some default value, but would it cause collisions in DKV if train algorithm multiple times? |
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Good points on the last comments:
Don't know, maybe @wendycwong knows?
What I meant generating a unique DKV name and setting it to the default value of the parameter( if that's possible). So a user could get the name via the algorithm parameter. But it's true that in some real edge cases even this key could become taken before we run the algo. But just thinking out loud. |
api-generation/src/main/scala/ai/h2o/sparkling/api/generation/common/IgnoredParameters.scala
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