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Feature Selection with Limited Bit Depth Mutual Information for Embedded Systems
2018
Proceedings (MDPI)
Data is growing at an unprecedented pace. With the variety, speed and volume of data flowing through networks and databases, newer approaches based on machine learning are required. But what is really big in Big Data? Should it depend on the numerical representation of the machine? Since portable embedded systems have been growing in importance, there is also increased interest in implementing machine learning algorithms with a limited number of bits. Not only learning, also feature selection,
doi:10.3390/proceedings2181187
fatcat:nsuv2xedkjbhlfq37xmbbshbpm