Decision tree is a data mining model that graphically represents the parameters that are most likely to influence the outcome and the extent of influence. The output is similar to a tree/flowchart with nodes, branches and leaves. The nodes represent the parameters, the branches represent the classification question/decision and the leaves represent the outcome (Screen Capture 1). Internally, decision tree algorithm performs a recursive classification on the input dataset and assigns each record to a segment of the tree where it fits closest.
There are several packages in R that generate decision trees. For this post, I am using the ctree() function available in party package. The data I am using as input is energy rating of household air conditioners.

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