Struct google_api_proto::google::cloud::automl::v1beta1::TablesDatasetMetadata

pub struct TablesDatasetMetadata {
    pub primary_table_spec_id: String,
    pub target_column_spec_id: String,
    pub weight_column_spec_id: String,
    pub ml_use_column_spec_id: String,
    pub target_column_correlations: BTreeMap<String, CorrelationStats>,
    pub stats_update_time: Option<Timestamp>,
}

Metadata for a dataset used for AutoML Tables.

Fields

primary_table_spec_id: String

Output only. The table_spec_id of the primary table of this dataset.

target_column_spec_id: String

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.

weight_column_spec_id: String

column_spec_id of the primary table’s column that should be used as the weight column, i.e. the higher the value the more important the row will be during model training. Required type: FLOAT64. Allowed values: 0 to 10000, inclusive on both ends; 0 means the row is ignored for training. If not set all rows are assumed to have equal weight of 1. NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

ml_use_column_spec_id: String

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.

target_column_correlations: BTreeMap<String, CorrelationStats>

Output only. Correlations between

[TablesDatasetMetadata.target_column_spec_id][google.cloud.automl.v1beta1.TablesDatasetMetadata.target_column_spec_id], and other columns of the

[TablesDatasetMetadataprimary_table][google.cloud.automl.v1beta1.TablesDatasetMetadata.primary_table_spec_id]. Only set if the target column is set. Mapping from other column spec id to its CorrelationStats with the target column. This field may be stale, see the stats_update_time field for for the timestamp at which these stats were last updated.

stats_update_time: Option<Timestamp>

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.

Trait Implementations

impl Clone for TablesDatasetMetadata

fn clone(&self) -> TablesDatasetMetadata

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for TablesDatasetMetadata

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for TablesDatasetMetadata

fn default() -> Self

Returns the “default value” for a type.

impl Message for TablesDatasetMetadata

fn encoded_len(&self) -> usize

Returns the encoded length of the message without a length delimiter.

fn clear(&mut self)

Clears the message, resetting all fields to their default.

fn encode(&self, buf: &mut impl BufMut) -> Result<(), EncodeError>

where Self: Sized,

Encodes the message to a buffer.

fn encode_to_vec(&self) -> Vec<u8>

where Self: Sized,

Encodes the message to a newly allocated buffer.

fn encode_length_delimited( &self, buf: &mut impl BufMut, ) -> Result<(), EncodeError>

where Self: Sized,

Encodes the message with a length-delimiter to a buffer.

fn encode_length_delimited_to_vec(&self) -> Vec<u8>

where Self: Sized,

Encodes the message with a length-delimiter to a newly allocated buffer.

fn decode(buf: impl Buf) -> Result<Self, DecodeError>

where Self: Default,

Decodes an instance of the message from a buffer.

fn decode_length_delimited(buf: impl Buf) -> Result<Self, DecodeError>

where Self: Default,

Decodes a length-delimited instance of the message from the buffer.

fn merge(&mut self, buf: impl Buf) -> Result<(), DecodeError>

where Self: Sized,

Decodes an instance of the message from a buffer, and merges it into self.

fn merge_length_delimited(&mut self, buf: impl Buf) -> Result<(), DecodeError>

where Self: Sized,

Decodes a length-delimited instance of the message from buffer, and merges it into self.

impl PartialEq for TablesDatasetMetadata

fn eq(&self, other: &TablesDatasetMetadata) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

This method tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for TablesDatasetMetadata