Data Quality Reports | Linear Regression | Vantage Analytics Library - Data Quality Reports - Vantage Analytics Library

Constant Variables

Before building a model, the linear function checks if any variable has a constant value (that is, a standard deviation of zero). If so, the function stops, notifies you, and outputs a Constant Variables Table report. You can remove the constant variables from the model and rerun the function.

The Constant Variables Table report can include variables that do not have constant values in the data. The cause is a column (or multiple columns) with values that are extremely large and very close, where precision loss causes the standard deviation to appear to be zero. Correct this problem by rescaling the values in such columns before matrix building or analysis, using the transformation function Rescale or Z-Score.

Variable Statistics

If statstable=true, the linear function includes in the XML output string a report that includes the mean value and standard deviation of each model variable, derived from the ESSCP matrix built by the function or provided as input.

Near Dependency

If neardependencyreport=true, the linear function includes in the XML output string a report that shows columns that may be collinear, with their variance proportions, means, and standard deviations. The Near Dependency report greatly simplifies the search for collinear variables or near dependencies in the data. You can specify the thresholds for the condition index and variance proportion.

In the report, near dependencies are in descending order based on their condition index value and variables contributing to a near dependency are in descending order based on their variance proportion.

Here is an example of a Near Dependency report: