一种正则化特征选择框架在桌面网格上的部署

A. Barla, M. Ferrante
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引用次数: 1

摘要

我们提出了一种廉价的解决方案来克服最先进的特征选择框架的计算挑战。该算法依赖于两个嵌套的交叉验证循环,允许对正则化参数进行最佳选择,从而导致计算代价高昂的过程。为了加快这一过程,我们在一个桌面网格设施上执行循环,该设施部署在计算机机房的pc上,作为通过VPN连接的虚拟机。本地网格与其他北意大利大学管理的类似网格共享资源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Deployment of a Regularized Feature Selection Framework on an Overlay Desktop Grid
We present an inexpensive solution to overcome the computational challenges of a state-of-the art feature selection framework. The algorithm relies on two nested loops of cross validation that allow the optimal choice for the regularization parameters resulting in a computationally expensive procedure. In order to speed up the process, we perform the loops on a desktop grid facility deployed on PCs in computer rooms as virtual machines connected through a VPN. The local grid shares resources with similar grids managed by other North Italian universities.
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