TESTING DECISION TREE ALGORITHM USING TANAGRA APPLICATIONS
Abstract
Decision tree is one algorithm that is used to classify segmentation or grouping which is predictive, Decision Tree Algorithm has the Advantages in processing numerical (continuous) and discrete data, can handle missing attribute values, produces rules that are easily interpreted and the fastest among other algorithms. Prediction accuracy is the ability of the model to be able to predict class labels against new or previously unknown data well. In terms of speed or computational time efficiency needed to create and use a model. The application used is Tanagra because the application is available for Decision tree architecture.
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