A Scalable Feature Selection and Model Updating Approach for Big Data Machine Learning

@article{Yang2016ASF,
  title={A Scalable Feature Selection and Model Updating Approach for Big Data Machine Learning},
  author={Baijian Yang and Tonglin Zhang},
  journal={2016 IEEE International Conference on Smart Cloud (SmartCloud)},
  year={2016},
  pages={146-151}
}
In this paper, we proposed an innovative approach for feature selection and model updating in big data machine learning. Since hard drive access is the biggest barrier for big data problems, it is therefore nature to reduce disk I/O operations when evaluating different combinations of features, or updating a learning machine. Particularly, we are interested in discovering if small enough matrices exist to represent a system and if the calculation of such matrices can be achieved in a row-by-row… CONTINUE READING

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