Amplifying Inter-Message Distance: On Information Divergence Measures in Big Data

Message identification (M-I) divergence is an important measure of the information distance between probability distributions, similar to Kullback-Leibler (K-L) and Renyi divergence. In fact, M-I divergence with a variable parameter can make an effect on characterization of distinction between two d...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE access 2017-01, Vol.5, p.24105-24119
Hauptverfasser:	She, Rui, Liu, Shanyun, Fan, Pingyi
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Amplification Anomaly detection Big Data big data analysis Clustering Data analysis discrete distribution estimation Divergence divergence estimation Entropy Estimation Information theory Kernel Message identification (M-I) divergence outlier detection Outliers (statistics) Parameters Probability distribution Statistical analysis
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!