WhiteWine

<p>The WhiteWine data frame has 4898 rows and 12 columns and
  concerns white wines from a region in Portugal. The response 
  variable, quality, is a wine quality metric, taken to be the median
 preference score of three blind tasters on a scale of 1-10. The 11 covariates
 are physicochemical metrics of wine quality such as citric acid content, 
 sulphates, etc.</p>

datasets

Implements Individual Conditional Expectation (ICE) plots, a tool for visualizing the model estimated by any supervised learning algorithm. ICE plots refine Friedman's partial dependence plot by graphing the functional relationship between the predicted response and a covariate of interest for individual observations. Specifically, ICE plots highlight the variation in the fitted values across the range of a covariate of interest, suggesting where and to what extent they may exist.

Adam Kapelner

ICEbox

Individual Conditional Expectation Plot Toolbox

WhiteWine function

<p>A data frame of 4898 cases on 12 variables.</p>

WhiteWine: Data concerning white wine.

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