Solution Path
The horizontal scaling for both plots is given in terms of the Magnitude of Scaled Parameter Estimates. This is the l1 norm, defined as the sum of the absolute values of the scaled parameter estimates for the model for the mean. (Estimates corresponding to the intercept, dispersion parameters, and zero-inflation parameters are excluded from the calculation of the l1 norm.) Note the following:
Estimates with large values of the l1 norm are close to the MLE.
Estimates with small values of the l1 norm are heavily penalized.
Current Model Indicator
A solid vertical red line is placed in both plots at the value of the l1 norm for the solution displayed in the Parameter Estimates for Original Predictors report. You can drag the arrow at the top of the vertical red line in either plot to change the magnitude of the penalty, indicating a new current model. In the Validation Plot, you can also click anywhere in the plot to change the model. As you drag the vertical red line to indicate a new model, the results in the report update to reflect the currently selected model. A dashed vertical line remains at the best fit model. For some validation methods, the Validation Plot provides zones that identify comparable models. See Comparable Model Zones.
Solution Path Report for, Lasso with AICc Validation
Solution Path Plot
The Parameter Estimates are plotted using the vertical axis of the Solution Path Plot. These are the scaled parameter estimates. They are derived for a model expressed in terms of centered and scaled predictors (see Parameter Estimates for Centered and Scaled Predictors).
The Solution ID
Validation Plot
The Validation Plot shows plots of statistics that describe how well models fit across the values of the tuning parameter, or equivalently, across the values of the Magnitude of the Scaled Parameter Estimates. The statistics plotted depend on the selected Validation Method. For each Validation Method, Validation Methods and Corresponding Validation Statistics and Zones lists the statistic that is plotted. For all validation methods, smaller values are better. For the KFold and Leave-One-Out validation methods, and for a Validation Column with more than three values, the statistic that is plotted is the mean of the scaled negative log-likelihood values across the folds.
The Scaled -LogLikelihood in Validation Methods and Corresponding Validation Statistics and Zones is the negative log-likelihood divided by the number of observations in the set for which the negative log-likelihood is computed.
Validation Plot for, Lasso with AICc Validation shows a Validation Plot for with the vertical axis expanded to show the two zones.
Validation Plot for, Lasso with AICc Validation

Help created on 9/19/2017