Latu.ML.Feature.ImputerModel (latu_ml v0.2.0)

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Attributes of a fitted ImputerModel.

Every accessor here is one name on the server's allowlist for org.apache.spark.ml.feature.ImputerModel — 1 of them — so tab completion is that allowlist. The server refuses anything else with CONNECT_ML.ATTRIBUTE_NOT_ALLOWED; these refuse a model of the wrong class before it gets that far, and name the module that would have taken it.

Allowed by the server but not here: toString is Identifiable's, and tells you less than the model's own uid. Latu.ML.attribute/2 and Latu.ML.attribute/3 will send any of these names; it is what comes back that has nowhere to go.

The allowlist is inherited rather than per class: this one is the union of org.apache.spark.ml.feature.ImputerModel, org.apache.spark.ml.util.Identifiable.

Summary

Functions

The JVM class these accessors belong to.

Returns a DataFrame containing inputCols and their corresponding surrogates, which are used to replace the missing values in the input DataFrame.

Functions

class()

@spec class() :: String.t()

The JVM class these accessors belong to.

surrogate_df(holder)

@spec surrogate_df(Latu.ML.Model.t()) :: Latu.DataFrame.t()

Returns a DataFrame containing inputCols and their corresponding surrogates, which are used to replace the missing values in the input DataFrame.

A lazy builder: the Fetch rides a relation, so this hands back a Latu.DataFrame and nothing has run until you collect it.