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中文摘要：
区间型数据（Interval data,ID）是属性特征取值为区间的一类数据,针对区间型数据的分类问题,本文提出一种高斯区间核支持向量机分类模型（Support vector machine based on Gauss interval kernel,GIK_SVM）。该方法引入半宽因子,在区间型数据的中值与半宽度之间进行折中,并据此构造高斯区间核用以衡量两个区间型数据间的相似性,然后用SVM模型进行分类。在人造数据集和真实数据集上的实验结果表明,本文提出的算法对区间数据有更好的分类性能。
英文摘要：
Interval data（ID）is a kind of data which the attribute values are the interval.Aiming at the classification problem of interval data,a support vector machine classification model based on Gauss interval kernel（GIK_SVM）is proposed.In the method,the half-width factor is introduced which makes a compromise between the median and the half width of interval data.Then,the Gauss interval kernel is constructed to measure the similarity between two interval data.SVM model is applied to classify the samples.Experiment results on artificial and real datasets demonstrate that the proposed GIK_SVM has a better classification performance for interval data.
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