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Improvement of SLIQ Algorithm and its Application in Evaluation

机译:SLIQ算法的改进及其在评估中的应用

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In view of the high operation cost of Gini index for SLIQ algorithm while searching the optimal split scheme, and from the objective distribution of data, the thesis introduces the concept of Density of Data Distribution. The new SLIQ algorithm, improved on the base of Gini index, is adopted in synthetic evaluation. The results in the example demonstrate that the number of the Gini index is reduced greatly after the improvement of SLIQ algorithm while searching the optimal split scheme. The cost of sorting and the optimal split point is also cut down. So the size of decision tree is simplified. Thus the evaluating objectives are classified, and the evaluating results are arranged in order and then the ordering and classified synthetic evaluation is realized.
机译:鉴于SLIQ算法的GINI指数的高运行成本在搜索最佳分流方案的同时,以及从数据的客观分布,论文介绍了数据分布密度的概念。在合成评估中采用了新的SLIQ算法,改进了基尼指数的基础。该示例中的结果表明,在搜索最佳分流方案的同时改进SLIQ算法之后,GINI指数的数量大大减少。分类成本和最佳分裂点也被削减。因此,简化了决策树的大小。因此,评估目标被分类,并且评估结果按顺序排列,然后实现排序和分类的合成评估。

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