The following tables and options are available for Linear-AS visualizations.
Model Information table
This table identifies the model type, target, and the number of features or predictors.
Predictor Importance chart
This chart displays bars representing the predictors in descending order of relative importance for predicting the target, as determined by a variance-based sensitivity analysis algorithm. The values for each predictor are scaled so that they add to 1. Hovering over the bar for a particular predictor shows a table with its importance value and descriptive statistics about the predictor.
This table displays the parameter estimates (also known as regression coefficients, beta coefficients or beta weights) for the fitted linear model. These are the values used in constructing the prediction equation for the linear model. They are expressed in raw or unstandardized form, so in comparing their relative sizes, you have to take into account the scales of the relevant features.
Like your visualization? Why not deploy it? For more information, see Deploy a model.