TY - CHAP
T1 - Traditional machine learning
AU - Liu, Han
AU - Cocea, Mihaela
N1 - Publisher Copyright:
© 2018, Springer International Publishing AG.
PY - 2017/11/5
Y1 - 2017/11/5
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85100563776&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-70058-8_2
DO - 10.1007/978-3-319-70058-8_2
M3 - Chapter (peer-reviewed)
AN - SCOPUS:85100563776
SN - 9783319700571
T3 - Studies in Big Data
SP - 11
EP - 22
BT - Granular Computing Based Machine Learning
PB - Springer
ER -