Metadata for a dataset used for AutoML Tables.
column_spec_id of the primary table's column that should be used as the training & prediction target. This column must be non-nullable and have one of following data types (otherwise model creation will error): - CATEGORY - FLOAT64 If the type is CATEGORY , only up to 100 unique values may exist in that column across all rows. NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.
column_spec_id of the primary table column which specifies a
possible ML use of the row, i.e. the column will be used to
split the rows into TRAIN, VALIDATE and TEST sets. Required
type: STRING. This column, if set, must either have all of
TRAIN, VALIDATE, TEST among its values, or only
have TEST, UNASSIGNED values. In the latter case the
rows with UNASSIGNED value will be assigned by AutoML.
Note that if a given ml use distribution makes it impossible
to create a "good" model, that call will error describing the
issue. If both this column_spec_id and primary table's
time_column_spec_id are not set, then all rows are treated
as UNASSIGNED. NOTE: Updates of this field will instantly
affect any other users concurrently working with the dataset.
Output only. The most recent timestamp when target_column_correlations field and all descendant ColumnSpec.data_stats and ColumnSpec.top_correlated_columns fields were last (re-)generated. Any changes that happened to the dataset afterwards are not reflected in these fields values. The regeneration happens in the background on a best effort basis.
Classes
TargetColumnCorrelationsEntry
API documentation for automl_v1beta1.types.TablesDatasetMetadata.TargetColumnCorrelationsEntry class.