Struct gapi_grpc::google::cloud::automl::v1beta1::TablesDatasetMetadata [−][src]
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: HashMap<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
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fn clone(&self) -> TablesDatasetMetadata
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pub fn clone_from(&mut self, source: &Self)
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impl Debug for TablesDatasetMetadata
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impl Default for TablesDatasetMetadata
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fn default() -> TablesDatasetMetadata
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impl Message for TablesDatasetMetadata
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fn encode_raw<B>(&self, buf: &mut B) where
B: BufMut,
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B: BufMut,
fn merge_field<B>(
&mut self,
tag: u32,
wire_type: WireType,
buf: &mut B,
ctx: DecodeContext
) -> Result<(), DecodeError> where
B: Buf,
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&mut self,
tag: u32,
wire_type: WireType,
buf: &mut B,
ctx: DecodeContext
) -> Result<(), DecodeError> where
B: Buf,
fn encoded_len(&self) -> usize
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fn clear(&mut self)
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pub fn encode<B>(&self, buf: &mut B) -> Result<(), EncodeError> where
B: BufMut,
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B: BufMut,
pub fn encode_length_delimited<B>(&self, buf: &mut B) -> Result<(), EncodeError> where
B: BufMut,
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B: BufMut,
pub fn decode<B>(buf: B) -> Result<Self, DecodeError> where
Self: Default,
B: Buf,
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Self: Default,
B: Buf,
pub fn decode_length_delimited<B>(buf: B) -> Result<Self, DecodeError> where
Self: Default,
B: Buf,
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Self: Default,
B: Buf,
pub fn merge<B>(&mut self, buf: B) -> Result<(), DecodeError> where
B: Buf,
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B: Buf,
pub fn merge_length_delimited<B>(&mut self, buf: B) -> Result<(), DecodeError> where
B: Buf,
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B: Buf,
impl PartialEq<TablesDatasetMetadata> for TablesDatasetMetadata
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fn eq(&self, other: &TablesDatasetMetadata) -> bool
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fn ne(&self, other: &TablesDatasetMetadata) -> bool
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impl StructuralPartialEq for TablesDatasetMetadata
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Auto Trait Implementations
impl RefUnwindSafe for TablesDatasetMetadata
impl Send for TablesDatasetMetadata
impl Sync for TablesDatasetMetadata
impl Unpin for TablesDatasetMetadata
impl UnwindSafe for TablesDatasetMetadata
Blanket Implementations
impl<T> Any for T where
T: 'static + ?Sized,
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T: 'static + ?Sized,
impl<T> Borrow<T> for T where
T: ?Sized,
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T: ?Sized,
impl<T> BorrowMut<T> for T where
T: ?Sized,
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T: ?Sized,
pub fn borrow_mut(&mut self) -> &mut T
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impl<T> From<T> for T
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impl<T> Instrument for T
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pub fn instrument(self, span: Span) -> Instrumented<Self>
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pub fn in_current_span(self) -> Instrumented<Self>
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impl<T> Instrument for T
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pub fn instrument(self, span: Span) -> Instrumented<Self>
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pub fn in_current_span(self) -> Instrumented<Self>
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impl<T, U> Into<U> for T where
U: From<T>,
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U: From<T>,
impl<T> IntoRequest<T> for T
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pub fn into_request(self) -> Request<T>
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impl<T> ToOwned for T where
T: Clone,
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T: Clone,
type Owned = T
The resulting type after obtaining ownership.
pub fn to_owned(&self) -> T
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pub fn clone_into(&self, target: &mut T)
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impl<T, U> TryFrom<U> for T where
U: Into<T>,
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U: Into<T>,
type Error = Infallible
The type returned in the event of a conversion error.
pub fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>
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impl<T, U> TryInto<U> for T where
U: TryFrom<T>,
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U: TryFrom<T>,
type Error = <U as TryFrom<T>>::Error
The type returned in the event of a conversion error.
pub fn try_into(self) -> Result<U, <U as TryFrom<T>>::Error>
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impl<V, T> VZip<V> for T where
V: MultiLane<T>,
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V: MultiLane<T>,
impl<T> WithSubscriber for T
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pub fn with_subscriber<S>(self, subscriber: S) -> WithDispatch<Self> where
S: Into<Dispatch>,
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S: Into<Dispatch>,