Onscreen Output
Column | Description |
---|---|
dfDevRatio | Number of nonzero coefficients for DevRatio in each lambda value. |
DevRatio | Fraction of (null) deviance explained. Deviance calculations incorporate weights if present in the model. Therefore, this value is (1-deviance)/(null deviance). (For elastic net, this value is the R-square.) |
dfDev | Number of nonzero coefficients for deviance in each lambda value. |
deviance | Deviance, which is defined as 2*(loglike_sat - loglike), where loglike_sat is the log-likelihood for the saturated model (a model with a free parameter for each observation). |
lambda | Lambda value. |
Model Table
Column | Data Type | Description |
---|---|---|
group | VARCHAR | Contains the abstract categories for output, which are:
|
information | VARCHAR | Contains the values provided in either this column or the value column (for example, FAMILY:POISSON). |
value | VARCHAR, INTEGER, or DOUBLE PRECISION | Contains the value of each item specified in the information column. |
Regularization Table
The function outputs this table only if you specify the RegularizationTable argument.
Column | Data Type | Description |
---|---|---|
df_dev_ratio | DOUBLE PRECISION | Number of nonzero coefficients for %dev in each lambda value. |
deviance_ratio | DOUBLE PRECISION | Fraction of (null) deviance explained. Deviance calculations incorporate weights if present in the model. Therefore, this value is (1-deviance)/(null deviance). (For elastic net, this value is the R-square.) |
df_dev | DOUBLE PRECISION | Number of nonzero coefficients for deviance in each lambda value. |
deviance | DOUBLE PRECISION | Deviance, which is defined as 2*(loglike_sat - loglike), where loglike_sat is the log-likelihood for the saturated model (a model with a free parameter for each observation). |
lambda | DOUBLE PRECISION | Lambda value. |
predictor_variable_column | DOUBLE PRECISION | Coefficients for all predictors for the current lambda value. |