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- W2969384402 abstract "Decision trees are data structures or computational methods that enable nonparametric supervised machine learning and are used in classification and regression tasks. The aim of this paper is to present a comparison between the decision tree induction algorithms C4.5 and CART. A quantitative study is performed in which the two methods are compared by analyzing the following aspects: operation and complexity. The experiments presented practically equal hit percentages in the execution time for tree induction, however, the CART algorithm was approximately 46.24% slower than C4.5 and was considered to be more effective." @default.
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- W2969384402 date "2019-08-24" @default.
- W2969384402 modified "2023-09-26" @default.
- W2969384402 title "Analysis of Decision Tree Induction Algorithms" @default.
- W2969384402 doi "https://doi.org/10.33448/rsd-v8i11.1473" @default.
- W2969384402 hasPublicationYear "2019" @default.
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