7.00.02 - Input - Aster Analytics

Teradata Aster® Analytics Foundation User GuideUpdate 2

Product
Aster Analytics
Release Number
7.00.02
Published
September 2017
Content Type
Programming Reference
User Guide
Publication ID
B700-1022-700K
Language
English (United States)
Last Update
2018-04-17

Single decision trees support millions of attributes. Because the database cannot have millions of columns, you must spread the attributes across rows in the form of key-value pairs, where key is the name of the attribute and value is the value of the attribute. The Unpivot function is useful for this purpose (see Example 1).

The Single_Tree_Drive function requires either an input table or both an attribute table and a response table. The function has two optional input tables, the splits table and the categorical splits table.

If the function encounters an input table row with missing values, it issues an error message.
Single_Tree_Drive Input Table Schema
Column Name Data Type Description
id_column Any Data point identifier. Cannot be NULL.
attribute_column VARCHAR Attribute name. Cannot be NULL.

Every attribute in the attribute table must be given a non-empty partition in the splits table.

node_column

Numeric attribute:

NUMERIC, INTEGER, BIGINT, or DOUBLE PRECISION

Categorical attribute:

Any

Attribute value. Can be NULL, in which case the function estimates its value by arithmetic means on an attribute basis. If this value is out of range, the function cannot use it to partition the training data; therefore, it is useless.
response_column NUMERIC, INTEGER, BIGINT, or DOUBLE PRECISION Response value for the data point. Can be NULL.
weight_column DOUBLE PRECISION Weight of the data point. Cannot be NULL. This column appears only if the decision tree is weighted.
actual_label VARCHAR Actual label of data point.
Single_Tree_Drive Attribute Table Schema
Column Name Data Type Description
id_column Any Data point identifier. Cannot be NULL.
attribute_column VARCHAR Attribute name. Cannot be NULL.

Every attribute in the attribute table must be given a non-empty partition in the splits table.

node_column

Numeric attribute:

NUMERIC, INTEGER, BIGINT, or DOUBLE PRECISION

Categorical attribute:

Any

Attribute value. Can be NULL, in which case the function estimates its value by arithmetic means on an attribute basis. If this value is out of range, the function cannot use it to partition the training data; therefore, it is useless.
actual_label VARCHAR Actual label of data point.
Single_Tree_Drive Response Table Schema
Column Name Data Type Description
id_column Any Data point identifier. Cannot be NULL.
response_column NUMERIC, INTEGER, BIGINT, or DOUBLE PRECISION Response value for the data point. Can be NULL.
weight_column DOUBLE PRECISION Weight of the data point. Cannot be NULL. This column appears only if the decision tree is weighted.
The response table must not have a column named node_id.
Single_Tree_Drive Splits Table Schema
Column Name Data Type Description
attribute_column VARCHAR Attribute name. Cannot be NULL.

Every attribute in the attribute table must be given a non-empty partition in the splits table.

split_id INTEGER Split identifier. Cannot be NULL.
splits_valcol NUMERIC, INTEGER, BIGINT, or DOUBLE PRECISION Split value. Cannot be NULL.
Single_Tree_Drive Categorical Splits Table Schema
Column Name Data Type Description
attribute VARCHAR Categorical attribute name.