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Determination of accuracy value in id3 algorithm with gini index and gain ratio with minimum size for split,minimum leaf size,and minimum gain

机译:基尼索引和最小尺寸的ID3算法中ID3算法中精度值的测定,最小尺寸和最小增益

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A process that explains and functions to distinguish data classes is called Classification.The use of Gain Ratio in ID3 algorithm is very influential on accuracy compared to the Gini Index,and if the higher the determination of the minimum size of split,the minimum leaf size and the minimum gain,the accuracy results will be greater in the gini index and gain ratio,but from both methods there is an accuracy difference of 27% for each accuracy test.In determining the minimum size of split 2,the minimum leaf size 2 and the minimum gain 0.4 with the value of accuracy at the gain ratio of 85.53% and gini index 58.67%.The minimum size of split 6,the minimum leaf size 3 and the minimum gain 0.8 with accuracy values at gain ratio 64.67% and gini index 60.67%.Then the minimum size of split 12,the minimum leaf size 6 and the minimum gain of 0.16 with the value of accuracy at the gain ratio of 86.00% and the index of 68.00%.While the minimum size of split 48,the minimum leaf size 24 and the minimum gain of 0.64 with the value of accuracy at the gain ratio of 95.33% and the index value of 72.00%.Then the Gain ratio which produces the highest accuracy value compared to the gini index.
机译:解释和用于区分数据类的过程称为分类。与基尼指数相比,ID3算法中的增益比的使用是非常有影响力的,并且如果较小的分裂尺寸的确定越高,则最小叶片尺寸并且最小的增益,精度结果在基尼指数和增益比中更大,但是从两种方法都有27%的精度差,每个精度测试都有27%。在确定分裂2的最小尺寸,最小叶片尺寸2并且最小增益0.4,增益比率为85.53%的准确度和基尼指数58.67%。分裂6的最小尺寸,最小叶片尺寸3和最小增益0.8,增益比率为64.67%和基尼的精度值索引60.67%。该分裂12的最小尺寸,最小叶片尺寸6和最小增益为0.16,最低值的增益比率为86.00%,指数为68.00%。拆分48的最小尺寸,最小叶尺寸24和最小值UM增益为0.64,增益比率为95.33%,指数值为72.00%。该增益比与基尼指数相比产生最高精度值。

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