Methods of Machine Learning

Volker Liermann () and Sangmeng Li ()
Additional contact information
Volker Liermann: ifb SE
Sangmeng Li: ifb SE

A chapter in The Digital Journey of Banking and Insurance, Volume III, 2021, pp 225-238 from Springer

Abstract: Abstract The article refers to the book “The Impact of Digital Transformation and Fintech on the Finance Professional”, more specifically to chapter 16, “Mathematical Background of Machine Learning”. Some additional methods used and presented in this book serve as an addition to the methods presented in the previous book. The topics focused on are model validation, imbalanced data and model interpretability.

Keywords: Machine Learning; Deep Learning; Model Validation; Imbalanced Data; Model Interpretability (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations: View citations in EconPapers (27)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-78821-6_13

Ordering information: This item can be ordered from
http://www.springer.com/9783030788216

DOI: 10.1007/978-3-030-78821-6_13

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().