5.4.5 - Logistic Regression Graphs - 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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The Logistic Regression analysis can display bar chars for the T-statistics, Wald Statistics, Log Odds Ratios, Partial R and Estimated Standard Coefficients of the resultant model. In addition, a Lift Chart in deciles is generated.

Logistic Weights Graph

This graph displays the relative magnitudes of the T-statistics, Wald Statistics, Log Odds Ratios, Partial R and Estimated Standard Coefficients associated with each variable in the logistic regression model. The sign, positive or negative, is portrayed by the colors red or blue respectively. The user may scroll to the left or right to see all the variables associated statistics in the model.

The following options are available on the Graphics Options tab on the Logistic Weights graph:
  • Graph Type — The following can be graphed by the Linear Weights Graph
    • Vertical Axis — The user may request multiple vertical axes in order to display separate coefficient values that are orders of magnitude different from the rest of the values. If the coefficients are of roughly the same magnitude, this option is grayed out.
    • Single — Display the selected statistics on single axis on the bar chart.
    • Multiple — Display the selected statistics on dual axes on the bar chart.

See Logistics Weight Graph for more information.

Lift Chart

This graph displays the statistics in the Cumulative Lift Table, with the following options:
  • Non-Cumulative
    • % Response — This column contains the percentage of observations in the decile where the actual value of the dependent variable is 1.
    • % Captured Response — This column contains the percentage of responses in the decile over all the responses in any decile.
    • Lift — The lift value is the percentage response in the decile (Pct Response) divided by the expected response, where the expected response is the percentage of response or dependent 1-values over all observations. For example, if 10% of the observations overall have a dependent variable with value 1, and 20% of the observations in decile 1 have a dependent variable with value 1, then the lift value within decile 1 is 2.0, meaning that the model gives a “lift” that is better than chance alone by a factor of two in predicting response values of 1 within this decile.
  • Cumulative
    • % Response — This is a cumulative measure of the percentage of observations in the decile where the actual value of the dependent variable is 1, from decile 1 to this decile.
    • % Captured Response — This is a cumulative measure of the percentage of responses in the decile over all the responses in any decile, from decile 1 to this decile.
    • Cumulative Lift — This is a cumulative measure of the percentage response in the decile (Pct Response) divided by the expected response, where the expected response is the percentage of response or dependent 1-values over all observations, from decile 1 to this decile.

See Lift Chart for more information.