Identifying Car Acceptability Using C5.0 Decision Trees and Rules by Ruby Suarez, Sonoma State University
The C5.0 decision tree algorithm and rule learners are two machine learning methods that also make complex decisions from sets of simple choices. Decision tree learners are powerful classifiers, which utilize a tree structure to model the relationship among the features and potential outcomes. Decision trees are built using a technique called recursive partitioning, also known as divide and conquer which splits the data into subsets which then split into even smaller subsets until the algorithm determines the data within the subsets are sufficiently homogenous.
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