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data_subset_table#
View page sourceThe Data Subset Table#
data_subset_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.
data_id#
This column has type integer
and is a
data_id in the data table.
These values are unique and monotone increasing with
data_subset_id .
This column identifies which rows of the
data_table are included in the fit_data_subset_table .
This is defined by the set of rows in the data
table
such that the following conditions hold:
Node#
The node is the Parent Node or a Descendant of the parent node.
Covariates#
All of the Covariates satisfy the max_difference criteria.
hold_out#
This column has type integer
.
If the value in this column is zero (one), the
corresponding data is (is not) included in subsequent fits.
The init_command initializes this column as zero.
The hold_out_command can be used to randomly choose
non-zero entries in this column.
This column is set to zero by the init_command .
density_id#
This column has type integer
.
It specifies which density is used for the corresponding data.
The init_command set it to be the same as the corresponding
density_id in the data table.
eta#
This column has type real
.
It specifies the value of eta used for the corresponding data.
The init_command set it to be the same as the corresponding
eta in the data table.
sample_size#
This column has type integer
.
It specifies the value of sample_size used for the corresponding data.
The init_command set it to be the same as the corresponding
sample_size in the data table.
nu#
This column has type real
.
It specifies the value of nu used for the corresponding data.
The init_command set it to be the same as the corresponding
nu in the data table.
Example#
See init_command.py example and test.