5.4.5 - Logistic Regression - INPUT - Data Selection - 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 Logistic Regression dialog box, click INPUT.
  2. Click data selection.
    Logistic Regression > Input > Data Selection

  3. On this screen, select:
    • Select Input Source — Users can select between different sources of input.
      By selecting the Input Source Table, the user can select from available databases, tables (or views) and columns in the usual manner. By selecting the Input Source Analysis, however, the user can select directly from the output of another analysis of qualifying type in the current project. Analyses that may be selected from directly include all of the Analytic Data Set (ADS) and Reorganization analyses (except Refresh). In place of Available Databases, the user can select from Available Analyses, while Available Tables contains a list of all the output tables that are eventually produced by the selected analysis.
      Since this analysis cannot select from a volatile input table, Available Analyses contains only those qualifying analyses that create an output table or view.
    • Select Columns From a Single Table
      • Available Databases (or Analyses) — All the databases (or analyses) that are available for the Logistic Regression analysis.
      • Available Tables — All the tables that are available for the Logistic Regression analysis.
      • Available Columns — Within the selected table or matrix, all columns which are available for the Logistic Regression analysis.
      • Selected Columns — Select columns by highlighting and then either dragging and dropping into the Selected Columns window, or click on the arrow button to move highlighted columns into the Selected Columns window.
        The Selected Columns window is actually a split window; you can either insert columns as Dependent or Independent columns. Make sure you have the correct portion of the window highlighted. The Dependent variable column is the column whose value is being predicted by the logistic regression model. The algorithm requires that the Independent columns must be of numeric type (or contain numbers in character format). The Dependent column may be of any type.