Title
On the Dynamics of Classification Measures for Imbalanced and Streaming Data
Abstract
As each imbalanced classification problem comes with its own set of challenges, the measure used to evaluate classifiers must be individually selected. To help researchers make this decision in an informed manner, experimental and theoretical investigations compare general properties of measures. However, existing studies do not analyze changes in measure behavior imposed by different imbalance ratios. Moreover, several characteristics of imbalanced data streams, such as the effect of dynamically changing class proportions, have not been thoroughly investigated from the perspective of different metrics. In this paper, we study measure dynamics by analyzing changes of measure values, distributions, and gradients with diverging class proportions. For this purpose, we visualize measure probability mass functions and gradients. In addition, we put forward a histogram-based normalization method that provides a unified, probabilistic interpretation of any measure over data sets with different class distributions. The results of analyzing eight popular classification measures show that the effect class proportions have on each measure is different and should be taken into account when evaluating classifiers. Apart from highlighting imbalance-related properties of each measure, our study shows a direct connection between class ratio changes and certain types of concept drift, which could be influential in designing new types of classifiers and drift detectors for imbalanced data streams.
Year
DOI
Venue
2020
10.1109/TNNLS.2019.2899061
IEEE Transactions on Neural Networks and Learning Systems
Keywords
DocType
Volume
Class imbalance,classification measures,concept drift,data streams,measure gradients,measure histograms
Journal
31
Issue
ISSN
Citations 
8
2162-237X
2
PageRank 
References 
Authors
0.36
20
4
Name
Order
Citations
PageRank
Dariusz Brzezinski121311.28
Jerzy Stefanowski21653139.25
Robert Susmaga337033.32
Izabela Szczęch4567.90