5.4.5 - Tree Scoring - RESULTS - Data - Teradata Warehouse Miner

Teradata Warehouse Miner User Guide - Volume 3Analytic Functions

Product
Teradata Warehouse Miner
Release Number
5.4.5
Published
February 2018
Language
English (United States)
Last Update
2018-05-04
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  1. On the Tree Scoring dialog box, click RESULTS.
  2. Click data (note that the RESULTS tab is disabled until after the analysis is completed).
    Tree Scoring > Results > Data

    Results data, if any, is displayed in a data grid.

    If a table was created, a sample of rows is displayed here - the size determined by the setting specified by Maximum result rows to display in Tools > Preferences > Limits.

    The following table is built in the requested Output Database by the Decision Tree Scoring analysis. Note that the options selected affect the structure of the table. Those columns in bold below comprise the Primary Index.
    There may be repeated groups of columns, and that some columns will be generated only if specific options are selected.
    Output Database table (Built by the Decision Tree Scoring analysis)
    Name Type Description
    Key User Defined One or more key columns, which default to the index, defined in the table to be scored (i.e., in Selected Table). The data type defaults to the same as the scored table, but can be changed via Primary Index Columns.
    <app_var> User Defined One or more columns as selected under Retain Columns.
    <dep_var >

    (Default)

    User Defined The predicted value of the dependent variable. The name used defaults to the Dependent Variable specified when the tree was built. If Use Dependent variable for predicted value column name is not selected, then an appropriate column name must be entered and is used here. The data type used is the same as the Dependent Variable.
    _tm_node_id FLOAT When the Create profiling tables option is selected this column is included to link each row with a particular leaf node in the decision tree and thereby with a specific set of rules.
    _tm_target, or

    _tm_confidence

    FLOAT One of two measures that are mutually exclusive. If the Include Confidence Factor option is selected, _tm_confidence is generated and populated with Confidence Factors - a measure of how “confident” the model is that it can predict the correct score for a record that falls into a particular leaf node based on the training data the model was built from.

    If the Targeted Confidence (Binary Outcome Only) option is selected, then _tm_target is generated and populated with Targeted Confidences for models built with a predicted value that has only 2 outcomes. The Targeted confidence is a measure of how confident the model is that it can predict the correct score for a particular leaf node based upon a user specified Target Value. For example, if a particular decision node had an outcome of 9 “Buys” and 1 “Do Not Buy” at that particular node, setting the Target Value to “Buy”, would generate a .9 or 9% targeted confidence. However, if Target Value is set to “Do Not Buy”, then any record falling into this leaf of the tree would get a targeted confidence of .1 or 10%.

    _tm_recalc_target, or

    _tm_recalc_confidence

    FLOAT Recalculated versions of the confidence factor or targeted confidence factor based on the original validation table when Score Only is selected, or based on the selected table to score when Evaluate and Score is selected.

    The following table is built in the requested Output Database by the Decision Tree Scoring analysis when the Create profiling tables option is selected. It is named by appending “_1” to the scored result table name.

    Output Database table (Built by the Decision Tree Scoring analysis) - Create profiling tables option selected (“_1” appended)
    Name Type Description
    _tm_node_id FLOAT This column identifies a particular leaf node in the decision tree.
    _tm_target, or

    _tm_confidence

    FLOAT The confidence factor or targeted confidence factor for this leaf node, as described above for the scored output table.
    _tm_prediction VARCHAR(n) The predicted value of the dependent variable at this leaf node.

    The following table is built in the requested Output Database by the Decision Tree Scoring analysis when the Create profiling tables option is selected. It is named by appending “_2” to the scored result table name.

    Output Database table (Built by the Decision Tree Scoring analysis) - Create profiling tables option selected (“_2” appended)
    Name Type Description
    _tm_node_id FLOAT This column identifies a particular leaf node in the decision tree.
    _tm_sequence_id FLOAT An integer from 1 to n to order the rules associated with a leaf node.
    _tm_rule VARCHAR(n) A rule for inclusion in the ruleset for this leaf node in the decision tree (rules are joined with a logical AND).