An empirical evaluation of the comprehensibility of decision table, tree and rule based predictive models

An important objective of data mining is the development of predictive models. Based on a number of observations, a model is constructed that allows the analysts to provide classifications or predictions for new observations. Currently, most research focuses on improving the accuracy or precision of these models and comparatively little research has been undertaken to increase their comprehensibility to the analyst or end-user. This is mainly due to the subjective nature of ‘comprehensibility’, which depends on many factors outside the model, such as the user's experience and his/her prior knowledge. Despite this influence of the observer, some representation formats are generally considered to be more easily interpretable than others. In this paper, an empirical study is presented which investigates the suitability of a number of alternative representation formats for classification when interpretability is a key requirement. The formats under consideration are decision tables, (binary) decision trees, propositional rules, and oblique rules. An end-user experiment was designed to test the accuracy, response time, and answer confidence for a set of problem-solving tasks involving the former representations. Analysis of the results reveals that decision tables perform significantly better on all three criteria, while post-test voting also reveals a clear preference of users for decision tables in terms of ease of use.     

A Pattern-Matching Compiler

Implementation of a rule-based transformation engine consists of several tasks with various abstraction levels. We present a new tool called mtom for the efficient implementation of rule-based transformations. This engine should help to bridge the gap between rewriting implementations and practical applications. It aims at implementing well-identified parts of complex applications where the use of rewriting is natural or crucial. These parts are specified using rewrite rules and integrated with the rest of the application, which is kept in a classical imperative language such as C, C++ or Java. Our tool, which can be viewed as a Yacc-like pre-processor, does not depend on a given term representation, rather it accepts implementation of terms (or term like data-types) of yet existing applications and it permits to define and execute rewrite rules upon those types. From our experiences, this system is well-suited for industrial use as well as for implementations of rule-based languages. The paper introduces several features supported by mtom.     

Robust detection of outliers for projection-based face recognition methods

In this paper, the impact of outliers on the performance of high-dimensional data analysis methods is studied in the context of face recognition. Most of the existing face recognition methods are based on PCA-like methods: faces are projected into a lower dimensional space in which similarity between faces is supposed to be more easily evaluated. These methods are, however, very sensitive to the quality of the face images used in the training and in the recognition phases. Their performance significantly drops when face images are not well centered or taken under variable illumination conditions. In this paper, we study this phenomenon for two face recognition methods, namely PCA and LDA2D, and we propose a filtering process that allows the automatic selection of noisy face images which are responsible for the performance degradation. This process uses two techniques. The first one is based on the recently proposed robust high-dimensional data analysis method called RobPCA. It is specific to the case of recognition from video sequences. The second technique is based on a novel and effective face classification technique. It allows isolating still face images that are not very precisely cropped, not well-centered or in a non-frontal pose. Experiments show that this filtering process significantly improves recognition rates by 10 to 30%.

A Secure Grid Medical Data Manager Interfaced to the gLite Middleware

The medical community is producing and manipulating a tremendous volume of digital data for which computerized archiving, processing and analysis is needed. Grid infrastructures are promising for dealing with challenges arising in computerized medicine but the manipulation of medical data on such infrastructures faces both the problem of interconnecting medical information systems to Grid middlewares and of preserving patients’ privacy in a wide and distributed multi-user system. These constraints are often limiting the use of Grids for manipulating sensitive medical data. This paper describes our design of a medical data management system taking advantage of the advanced gLite data management services, developed in the context of the EGEE project, to fulfill the stringent needs of the medical community. It ensures medical data protection through strict data access control, anonymization and encryption. The multi-level access control provides the flexibility needed for implementing complex medical use-cases. Data anonymization prevents the exposure of most sensitive data to unauthorized users, and data encryption guarantees data protection even when it is stored at remote sites. Moreover, the developed prototype provides a Grid storage resource manager (SRM) interface to standard medical DICOM servers thereby enabling transparent access to medical data without interfering with medical practice.     

Timed Specification For Web Services Compatibility Analysis

Web services are becoming one of the main technologies for designing and building complex inter-enterprise business applications. Usually, a business application cannot be fulfilled by one Web service but by coordinating a set of them. In particular, to perform a coordination, one of the important investigations is the compatibility analysis. Two Web services are said compatible if they can interact correctly. In the literature, the proposed frameworks for the services compatibility checking rely on the supported sequences of messages. The interaction of services depends also on other properties, such that the exchanged data flow. Thus, considering only supported sequences of messages seems to be insufficient. Other properties on which the services interaction can rely on, are the temporal constraints. In this paper, we focus our interest on the compatibility analysis of Web services regarding their (1) supported sequences of messages, (2) the exchanged data flow, (3) constraints related to the exchanged data flow and (4) the temporal requirements. Based on these properties, we study three compatibility classes: (i) absolute compatibility, (ii) likely compatibility and (iii) absolute incompatibility.     

Food vacuole proteome of the malarial parasite Plasmodium falciparum

The Plasmodium falciparum food vacuole (FV) is a lysosome-like organelle where erythrocyte hemoglobin digestion occurs. It is a favorite target in the development of antimalarials. We have used a tandem mass spectrometry approach to investigate the proteome of an FV-enriched fraction and identified 116 proteins. The electron microscopy analysis and the Western blot data showed that the major component of the fraction was the FV and, as expected, the majority of previously known FV markers were recovered. Of particular interest, several proteins involved in vesicle-mediated trafficking were identified, which are likely to play a key role in FV biogenesis and/or FV protein trafficking. Recovery of parasite surface proteins lends support to the cytostomal pathway of hemoglobin ingestion as a FV trafficking route. We have identified 32 proteins described as hypothetical in the databases. This insight into FV protein content provides new clues towards understanding the biological function of this organelle in P. falciparum.     

Optical information for car following: the driving by visual angle (DVA) model

OBJECTIVE: The present study developed and tested a model of car following by human drivers. BACKGROUND: Previous models of car following are based on 3-D parameters such as lead vehicle speed and distance information, which are not directly available to a driver. In the present paper we present the driving by visual angle (DVA) model, which is based on the visual information (visual angle and rate of change of visual angle) available to the driver. METHOD: Two experiments in a driving simulator examined car-following performance in response to speed variations of a lead vehicle defined by a sum of sine wave oscillations and ramp acceleration functions. In addition, the model was applied to six driving events using real world-driving data. RESULTS: The model provided a good fit to car-following performance in the driving simulation studies as well as in real-world driving performance. A comparison with the advanced interactive microscopic simulator for urban and nonurban networks (AIMSUN) model, which is based on 3-D parameters, suggests that the DVA was more predictive of driver behavior in matching lead vehicle speed and distance headway. CONCLUSION: Car-following behavior can be modeled using only visual information to the driver and can produce performance more predictive of driver performance than models based on 3-D (speed or distance) information. APPLICATION: The DVA model has applications to several traffic safety issues, including automated driving systems and traffic flow models.     

Uniting Local and Global Controllers with Robustness to Vanishing Noise

We consider control systems for which we know two stabilizing controllers. One is globally asymptotically stabilizing, the other one is only locally asymptotically stabilizing but for some reason we insist on using it in a neighborhood of the origin. We look for a uniting control law being equal to the local feedback on a neighborhood of the origin, equal to the global one outside of a larger neighborhood and being a globally stabilizing controller. We study several solutions based on continuous, discontinuous, hybrid, time-varying controllers. One criterion of the selection of a controller is the robustness of the stability to vanishing noise. This leads us in particular to consider a kind of generalization of Krasovskii trajectories for hybrid systems. Date received: November 29, 1999. Date revised: August 7, 2000.