Precision-recall operating characteristic (P-ROC) curves in imprecise environments

Traditionally, machine learning algorithms have been evaluated in applications where assumptions can be reliably made about class priors and/or misclassification costs. In this paper, we consider the case of imprecise environments, where little may be known about these factors and they may well vary significantly when the system is applied. Specifically, the use of precision-recall analysis is investigated and compared to the more well known performance measures such as error-rate and the receiver operating characteristic (ROC). We argue that while ROC analysis is invariant to variations in class priors, this invariance in fact hides an important factor of the evaluation in imprecise environments. Therefore, we develop a generalised precision-recall analysis methodology in which variation due to prior class probabilities is incorporated into a multi-way analysis of variance (ANOVA). The increased sensitivity and reliability of this approach is demonstrated in a remote sensing application.

Off-line signature verification and forgery detection system based on fuzzy modeling

This paper presents an innovative approach for signature verification and forgery detection based on fuzzy modeling. The signature image is binarized and resized to a fixed size window and is then thinned. The thinned image is then partitioned into a fixed number of eight sub-images called boxes. This partition is done using the horizontal density approximation approach. Each sub-image is then further resized and again partitioned into twelve further sub-images using the uniform partitioning approach. The features of consideration are normalized vector angle (α) from each box. Each feature extracted from sample signatures gives rise to a fuzzy set. Since the choice of a proper fuzzification function is crucial for verification, we have devised a new fuzzification function with structural parameters, which is able to adapt to the variations in fuzzy sets. This function is employed to develop a complete forgery detection and verification system.

Proceedings of the Eighth Australian and New Zealand Intelligent Information Systems Conference

These are the full proceedings of the conference.

The role of the innate immune system in the clearance of apoptotic cells

Rapid clearance of dying cells is a vital feature of apoptosis throughout development, tissue homeostasis and resolution of inflammation. The phagocytic removal of apoptotic cells is mediated by both professional and amateur phagocytes, armed with a series of pattern recognition receptors that participate in host defence and apoptotic cell clearance. CD14 is one such molecule. It is involved in apoptotic cell clearance (known to be immunosuppressive and anti-inflammatory) and binding of the pathogen-associated molecular pattern, lipopolysaccharides (a pro-inflammatory event). Thus CD14 is involved in the assembly of two distinct ligand-dependent macrophage responses. This project sought to characterise the involvement of the innate immune system, particularly CD14, in the removal of apoptotic cells. The role of non-myeloid CD14 was also considered and the data suggests that the expression of CD14 by phagocytes may define their professional status as phagocytes. To assess if differential CD14 ligation causes the ligand-dependent divergence in macrophage responses, a series of CD14 point mutants were used to map the binding of apoptotic cells and lipopolysaccharides. Monoclonal antibodies, 61D3 and MEM18, known to interfere with ligand-binding and responses, were also mapped. Data suggests that residue 11 of CD14, is key for the binding of 61D3 (but not MEM18), LPS and apoptotic cells, indicating lipopolysaccharides and apoptotic cells bind to similar residues. Furthermore using an NF-kB reporter, results show lipopolysaccharides but not apoptotic cells stimulate NF-kB. Taken together these data suggests ligand-dependent CD14 responses occur via a mechanism that occurs downstream of CD14 ligation but upstream of NF-?B activation. Alternatively apoptotic cell ligation of CD14 may not result in any signalling event, possibly by exclusion of TLR-4, suggesting that engulfment receptors, (e.g. TIM-4, BAI1 and Stablin-2) are required to mediate the uptake of apoptotic cells and the associated anti-inflammatory response.

The n-tuple classifier: too good to ignore

The n-tuple pattern recognition method has been tested using a selection of 11 large data sets from the European Community StatLog project, so that the results could be compared with those reported for the 23 other algorithms the project tested. The results indicate that this ultra-fast memory-based method is a viable competitor with the others, which include optimisation-based neural network algorithms, even though the theory of memory-based neural computing is less highly developed in terms of statistical theory.