Abstract Receiver Operating Characteristic (ROC) curves are a standard way to display the performance of a set of binary classifiers for all feasible ratios of the costs associated with …
S Ali, KA Smith - Applied Soft Computing, 2006 - Elsevier
This paper introduces a new method for learning algorithm evaluation and selection, with empirical results based on classification. The empirical study has been conducted among 8 …
This work is builds on the study of the 10 top data mining algorithms identified by the IEEE International Conference on Data Mining (ICDM) community in December 2006. We address …
P Geurts - Data mining and knowledge discovery handbook, 2010 - Springer
In this chapter, the important concepts of bias and variance are introduced. After an intuitive introduction to the bias/variance tradeoff, we discuss the bias/variance decompositions of …
A great many tools have been developed for supervised classification, ranging from early methods such as linear discriminant analysis through to modern developments such as …
VK Ayyadevara - Apress: Berkeley, CA, USA, 2018 - Springer
Machine learning techniques are being adopted for a variety of applications. With an increase in the adoption of machine learning techniques, it is very important for the …
RR Curtin, M Edel, M Lozhnikov… - Journal of Open …, 2018 - joss.theoj.org
In the past several years, the field of machine learning has seen an explosion of interest and excitement, with hundreds or thousands of algorithms developed for different tasks every …
C Drummond, RC Holte - Proceedings of the sixth ACM SIGKDD …, 2000 - dl.acm.org
This paper proposes an alternative to ROC representation, in which the expected cost of a classifier is represented explicitly. This expected cost representation maintains many of the …
Optimal performance is desired for decision-making in any field with binary classifiers and diagnostic tests, however common performance measures lack depth in information. The …