100% Classification Accuracy Considered Harmful: The Normalized Information Transfer Factor Explains the Accuracy Paradox

标题
100% Classification Accuracy Considered Harmful: The Normalized Information Transfer Factor Explains the Accuracy Paradox
作者
关键词
Entropy, Magnetoencephalography, Information entropy, Sports, Forecasting, Human performance, Machine learning, Discrete random variables
出版物
PLoS One
Volume 9, Issue 1, Pages e84217
出版商
Public Library of Science (PLoS)
发表日期
2014-01-11
DOI
10.1371/journal.pone.0084217

向作者/读者发起求助以获取更多资源

Reprint

联系作者

Find Funding. Review Successful Grants.

Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.

Explore

Discover Peeref hubs

Discuss science. Find collaborators. Network.

Join a conversation