Regression Report (Linear)

Regression report visualizer of the Linear regression component displays parameters and results of the statistical tests for the regression models analysis.

This visualizer consists of three areas:

More detailed infomation how to enable this visualizer is provided in the article.

Interface

Operations

Model Info Area

Regression Coefficients Area

Model Steps Area

Visualizer Areas

Model Info

Model indicators are described in the table:

Indicator Description
Logical Constant Dependent variable
Real -2 Log Likelihood -2 Logarithm of the likelihood function
Real R2 Determination coefficient
Real R2 adj. Determination coefficient adjusted
IntegerNumber of degrees of freedom Number of independently varied values of indicator
Real Significance Degree of statistic link of the input (set of the input ones) and output variables of regression model
Real AIC Akaike information criterion
Real AICc Akaike information criterion corrected
Real BIC Bayesian information criterion
Real HQC Hannan-Quinn information criterion

Regression Coefficients

Coefficients are described in the table:

Coefficient Description
Coefficient Characteristics of relation between dependent y and independent variable x
Standard error Measure of spread of the observation data from the modeled values
T-statistics Standard error ratio of the estimated coefficient to its absolute value
Significance Degree of statistic link of the input (set of the input ones) and output variables of regression model

Regression coefficients can be represented in the Table (refer to Figure 1) or Tree form (refer to Figure 2).

Table representation mode.
Figure 1. Table representation mode.
Tree representation mode.
Figure 2. Tree representation mode.

Model Steps

It is rational to enable the Steps construction area only if the algorithm that is based on the measure processing mode has been selected when configuring the Logistic Regression node in the Factor selection and protection against overfitting parameter.

Model steps area consists of the following fields:

Field Description
Model The tree of models in which the models created by the algorithm in the training process are displayed. It appears when measures are selected. Only one final model will be available in this field for the algorithms that do not support processing of measures. Clicking on the Model steps area with the left mouse button, it is possible to select display of the information on the selected model (if corresponding checkbox has been selected), and also regression coefficients.
Indicator Value of the selected indicator for the current model.
Field change It displays whether the measure has been added or deleted ("+" means that the measure has been added to the model, and "-" shows that the measure has been deleted from the model).
Fields Current model fields.

There are three model types:

  • Null model: the initial model of the algorithm operation.
  • Intermediate model: the model created by the algorithm in the training process.
  • Final model: the model that has been considered by the algorithm as the best one, and the further actions will not bring about the model improvement.

The indicators available for selection:

  • -2 Log Likelihood;
  • AIC;
  • AICc;
  • BIC;
  • HQC.

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