Attributes of a fitted MinMaxScalerModel.
Every accessor here is one name on the server's allowlist for
org.apache.spark.ml.feature.MinMaxScalerModel — 2 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.MinMaxScalerModel, org.apache.spark.ml.util.Identifiable.
Summary
Functions
The JVM class these accessors belong to.
Max value for each original column during fitting.
Min value for each original column during fitting.
Functions
@spec class() :: String.t()
The JVM class these accessors belong to.
@spec original_max(Latu.ML.Model.t()) :: {:ok, term()} | {:error, Latu.Error.t()}
Max value for each original column during fitting.
An action: it reaches the server. A Vector or Matrix comes back as an Nx.Tensor, or a
Latu.ML.SparseVector where densifying would be this package's decision rather than yours.
@spec original_min(Latu.ML.Model.t()) :: {:ok, term()} | {:error, Latu.Error.t()}
Min value for each original column during fitting.
An action: it reaches the server. A Vector or Matrix comes back as an Nx.Tensor, or a
Latu.ML.SparseVector where densifying would be this package's decision rather than yours.