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

Global Model Statistics for Logistic Regression

GLM generates global statistics for logistic regression, supporting model assessment.

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

  • Akaike's criterion for the fit of the intercept only model

  • Akaike's criterion for the fit of the intercept and the covariates (predictors) model

  • Schwarz's criterion for the fit of the intercept only model

  • Schwarz's criterion for the fit of the intercept and the covariates (predictors) model

  • -2 log likelihood of the intercept only model

  • -2 log likelihood of the model

  • Likelihood ratio degrees of freedom

  • Likelihood ratio chi-square probability value

  • Pseudo R-square Cox an Snell

  • Pseudo R-square Nagelkerke

  • Dependent mean

  • Percent of correct predictions

  • Percent of incorrect predictions

  • Percent of ties (probability for two cases is the same)

  • 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.