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regressionnode properties
regressionnode properties
Last updated: Feb 12, 2025
regressionnode properties

Regression node iconLinear regression is a common statistical technique for summarizing data and making predictions by fitting a straight line or surface that minimizes the discrepancies between predicted and actual output values.

Example

node = stream.create("regression", "My node")
# "Fields" tab
node.setPropertyValue("custom_fields", True)
node.setPropertyValue("target", "Age")
node.setPropertyValue("inputs", ["Na", "K"])
node.setPropertyValue("partition", "Test")
node.setPropertyValue("use_weight", True)
node.setPropertyValue("weight_field", "Drug")
# "Model" tab
node.setPropertyValue("use_model_name", True)
node.setPropertyValue("model_name", "Regression Age")
node.setPropertyValue("use_partitioned_data", True)
node.setPropertyValue("method", "Stepwise")
node.setPropertyValue("include_constant", False)
# "Expert" tab
node.setPropertyValue("mode", "Expert")
node.setPropertyValue("complete_records", False)
node.setPropertyValue("tolerance", "1.0E-3")
# "Stepping..." section
node.setPropertyValue("stepping_method", "Probability")
node.setPropertyValue("probability_entry", 0.77)
node.setPropertyValue("probability_removal", 0.88)
node.setPropertyValue("F_value_entry", 7.0)
node.setPropertyValue("F_value_removal", 8.0)
# "Output..." section
node.setPropertyValue("model_fit", True)
node.setPropertyValue("r_squared_change", True) 
node.setPropertyValue("selection_criteria", True)
node.setPropertyValue("descriptives", True)
node.setPropertyValue("p_correlations", True)
node.setPropertyValue("collinearity_diagnostics", True)
node.setPropertyValue("confidence_interval", True)
node.setPropertyValue("covariance_matrix", True)
node.setPropertyValue("durbin_watson", True)
Table 1. regressionnode properties
regressionnode Properties Values Property description
target field Regression models require a single target field and one or more input fields. A weight field can also be specified. See the topic Common modeling node properties for more information.
method
Enter
Stepwise
Backwards
Forwards
  
include_constant flag  
use_weight flag  
weight_field field  
mode
Simple
Expert
  
complete_records flag  
tolerance
1.0E-1
1.0E-2
1.0E-3
1.0E-4
1.0E-5
1.0E-6
1.0E-7
1.0E-8
1.0E-9
1.0E-10
1.0E-11
1.0E-12
 Use double quotes for arguments.
stepping_method
useP
useF
 useP : use probability of F useF: use F value
probability_entry number  
probability_removal number  
F_value_entry number  
F_value_removal number  
selection_criteria flag  
confidence_interval flag  
covariance_matrix flag  
collinearity_diagnostics flag  
regression_coefficients flag  
exclude_fields flag  
durbin_watson flag  
model_fit flag  
r_squared_change flag  
p_correlations flag  
descriptives flag  
calculate_variable_importance flag  
residuals boolean Statistics for the residuals (or the differences between predicted values and actual values).