利用机器学习技术预测最佳图划分策略

Proceedings of the 2018 VII International Conference on Network, Communication and Computing Pub Date : 2018-12-14 DOI:10.1145/3301326.3301354

Jiayi Shen, F. Huet

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引用次数: 3

摘要

在本文中，我们探索应用机器学习技术来寻找给定图的最佳分区。我们使用一些度量来描述图，并将这些度量作为输入，将图执行算法的分区排序作为标签来训练模型。我们的实验表明，KNN和决策树是解决这个问题的好模型。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Predict the Best Graph Partitioning Strategy by Using Machine Learning Technology

In this paper, we explore applying machine learning techniques to find a best partitioner for a given graph. We use some metrics to describe the graph, and use these metrics as the input and the partitioner ranking of a graph execution algorithm as the label to train a model. Our experiment shows KNN and decision tree are good models for this problem.

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Proceedings of the 2018 VII International Conference on Network, Communication and Computing

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