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Partly adaptive elastic net and its application to microarray classification

机译:部分自适应弹性网及其在微阵列分类中的应用

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This paper presents a new extension of the elastic net for simultaneous gene selection and microarray classification. By introducing the proper data-driven weights to the penalty terms, the partly adaptive elastic net is proposed, which can encourage an adaptive grouping effect and reduce the influence of the wrong initial estimation. A fast-solving algorithm is also developed in the line of pathwise coordinate descent. Experiments performed on the two cancer data sets are provided to verify the obtained results.
机译:本文介绍了弹性网的新扩展,可同时进行基因选择和微阵列分类。通过将适当的数据驱动权重引入惩罚项,提出了一种部分自适应的弹性网,可以鼓励自适应的分组效应,减少错误的初始估计的影响。在路径坐标下降线上也开发了一种快速求解算法。提供了在两个癌症数据集上进行的实验,以验证所获得的结果。

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