Predict the Best Graph Partitioning Strategy by Using Machine Learning Technology
Proceedings of the 2018 VII International Conference on Network, Communication and Computing（2018）
摘要
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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关键词
Machine learning, graph partition, metrics
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