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predict_table#
View page sourceThe Predict Table: Average Integrand Predictions#
See Also#
Purpose#
This table contains model predictions for the average integrand .
Avgint Subset#
For each row in the predict table, the avgint_id column below identifies the corresponding row in the avgint_table . Only a subset of the rows of the avgint table is included. The subset is defined by the following node and covariate conditions:
Node#
The node must be the Parent Node , or a Descendant of the parent node.
Covariates#
All of the Covariates must satisfy the max_difference criteria.
predict_id#
This column has type integer
and is the primary key for this table.
Its initial value is zero, and it increments by one for each row.
sample_index#
This column has type integer
and specifies the set of
model_variables that the avg_integrand corresponds to.
If source is
fit_var
or truth_var
, sample_index is null
(and the corresponding model variables are used).
Otherwise source is sample
and sample_index
is the corresponding value in the
sample_table .
This column is monotone non-decreasing; i.e. the value in each row
is greater than or equal the value in the previous row.
Each
sample_index value
in the sample table appears multiple times in the predict table,
once for each avgint_id in the
of the Avgint Subset .
avgint_id#
This column has type integer
and specifies the
avgint_id that
avg_integrand corresponds to.
For each sample_index value,
avgint_id is monotone increasing and includes every element
of the Avgint Subset .
avg_integrand#
This column type real
and is the
average integrand
\(A_i(u, \theta)\).
The model variables \((u, \theta)\) corresponding to the
model variables with sample_index in sample_table .
The subscript \(i\) denotes the
information in the avgint table for the specified
avgint_id .
Example#
The predict_command.py is an example that creates this table.