1,720,974 research outputs found
Glacier : guided locally constrained counterfactual explanations for time series classification
No full textIn machine learning applications, there is a need to obtain predictive models of high performance and, most importantly, to allow end-users and practitioners to understand and act on their predictions. One way to obtain such understanding is via counterfactuals, that provide sample-based explanations in the form of recommendations on which features need to be modified from a test example so that the classification outcome of a given classifier changes from an undesired outcome to a desired one. This paper focuses on the domain of time series classification, more specifically, on defining counterfactual explanations for univariate time series. We propose Glacier, a model-agnostic method for generating locally-constrained counterfactual explanations for time series classification using gradient search either on the original space or on a latent space that is learned through an auto-encoder. An additional flexibility of our method is the inclusion of constraints on the counterfactual generation process that favour applying changes to particular time series points or segments while discouraging changing others. The main purpose of these constraints is to ensure more reliable counterfactuals, while increasing the efficiency of the counterfactual generation process. Two particular types of constraints are considered, i.e., example-specific constraints and global constraints. We conduct extensive experiments on 40 datasets from the UCR archive, comparing different instantiations of Glacier against three competitors. Our findings suggest that Glacier outperforms the three competitors in terms of two common metrics for counterfactuals, i.e., proximity and compactness. Moreover, Glacier obtains comparable counterfactual validity compared to the best of the three competitors. Finally, when comparing the unconstrained variant of Glacier to the constraint-based variants, we conclude that the inclusion of example-specific and global constraints yields a good performance while demonstrating the trade-off between the different metrics. © The Author(s) 2024.This work was funded in part by the Digital Futures cross-disciplinary research centre in Sweden, and the EXTREMUM collaborative project ( https://datascience.dsv.su.se/projects/extremum.html ).</p
Assessment of double materiality
No full textSustainability reporting standards, e.g. the Global Reporting Initiative, require a broader definition of materiality than is traditionally used in financial reporting. Double materiality expands the material information concept to include information about companies' environmental and social impact relevant to society at large. A problem for reporting companies as well as auditors (even though accounting firms invest resources in establishing themselves as reliable service providers) is that the assessment of double materiality is uncertain. The chapter utilises machine learning methods to suggest a method to determine double materiality in sustainability reporting by examining what type of information can predict environmental issues resulting from companies' operations. It represents a proposal to use a structured and quantitative approach for sustainability auditors to determine double materiality, thereby potentially facilitating sustainability reporting and assurance in accordance with future regulation.</p
isaksamsten/wildboar: wildboar
No full textwildboar is a fast package for time series classification with Python
The package can be installed from PyPi
pip install wildboa
Code quality assessment using transformers
Get PDFAutomatically evaluate the correctness of programming assignments is rather
straightforward using unit and integration tests. However, programming tasks
can be solved in multiple ways, many of which, although correct, are inelegant.
For instance, excessive branching, poor naming or repetitiveness make the code
hard to understand and maintain. These subjective qualities of code are hard to
automatically assess using current techniques. In this work we investigate the
use of CodeBERT to automatically assign quality score to Java code. We
experiment with different models and training paradigms. We explore the
accuracy of the models on a novel dataset for code quality assessment. Finally,
we assess the quality of the predictions using saliency maps. We find that code
quality to some extent is predictable and that transformer based models using
task adapted pre-training can solve the task more efficiently than other
techniques
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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