1. Machine Learning for SQL Use Cases
  2. Concepts
  3. Machine Learning Algorithms
  4. About Generalized Linear Model
  5. Linear Regression
  6. Global Model Statistics for Linear Regression

Global Model Statistics for Linear Regression

Generalized Linear Model regression models generate the following statistics.

Generalized Linear Model regression models generate the following statistics that describe the model as a whole:

  • Model degrees of freedom

  • Model sum of squares

  • Model mean square

  • Model F statistic

  • Model F value probability

  • Error degrees of freedom

  • Error sum of squares

  • Error mean square

  • Corrected total degrees of freedom

  • Corrected total sum of squares

  • Root mean square error

  • Dependent mean

  • Coefficient of variation

  • R-Square

  • Adjusted R-Square

  • Akaike's information criterion

  • Schwarz's Baysian information criterion

  • Estimated mean square error of the prediction

  • Hocking Sp statistic

  • JP statistic (the final prediction error)

  • Number of parameters (the number of coefficients, including the intercept)

  • Number of rows

  • Whether or not the model converged

  • Whether or not a covariance matrix was computed