Traditional machine learning

Han Liu*, Mihaela Cocea

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

Abstract

In this chapter, we describe the concepts of traditional machine learning. In particular, we introduce the key features of supervised learning, heuristic learning, discriminative learning, single-task learning and random data partitioning. We also identify general issues of traditional machine learning, and discuss how traditional learning approaches can be impacted due to the presence of big data.

Original languageEnglish
Title of host publicationGranular Computing Based Machine Learning
PublisherSpringer
Pages11-22
Number of pages12
ISBN (Electronic)9783319700588
ISBN (Print)9783319700571
DOIs
Publication statusPublished - 5 Nov 2017

Publication series

NameStudies in Big Data
PublisherSpringer
Volume35
ISSN (Print)2197-6503
ISSN (Electronic)2197-6511

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