RT Journal Article
SR Electronic
T1 Machine Learning for Structured Finance
JF The Journal of Structured Finance
FD Institutional Investor Journals
SP 7
OP 25
DO 10.3905/jsf.2018.24.3.007
VO 24
IS 3
A1 Eric Kolchinsky
YR 2018
UL https://pm-research.com/content/24/3/7.abstract
AB Machine learning and artificial intelligence have evolved beyond simple hype and have integrated themselves in business and in popular conversation as an increasing number of smart applications profoundly transform the way we work and live. This article defines machine learning in terms of potential benefits and pitfalls for a nontechnical audience, and gives examples of popular and powerful machine learning algorithms: k-means clustering, principal component analysis, and artificial neural networks. Three important philosophical challenges of machine learning are introduced: the no free lunch theorem, the curse of dimensionality, and the bias–variance trade-off.TOPICS: Big data/machine learning, statistical methods