1,720,955 research outputs found
Effect of data preparation in the context of fair classification
No full textThis thesis investigates the critical role of data preparation in shaping the predictive performance and fairness of binary classification models. Given that the quality and composition of training data significantly influence model behaviour, especially concerning embedded biases, ensuring that training data is both accurate and fair is essential for the development of trustworthy machine learning systems. To address this, we extend an existing data processing pipeline, substantially broadening its data preparation stage with the integration of sixteen additional methods across five distinct components. This expansion allows for a more comprehensive evaluation of the interplay between data preparation, predictive accuracy, and algorithmic fairness.
Our empirical study employs a diverse set of classifiers and evaluation metrics, including several newly developed scores specifically designed to capture the nuanced effects of data preparation on model outcomes. The analysis spans both real-world and synthetic datasets, providing a robust foundation for our findings. Key insights include the observation that simply increasing the number of data preparation components does not necessarily improve model performance. Instead, optimal results often depend on carefully chosen methods and execution orders, with some components displaying strong positional dependencies. Additionally, our results reaffirm the well-documented trade-off between fairness and accuracy, yet also demonstrate that it is possible to identify configurations where both can be improved simultaneously.
These findings not only deepen our understanding of data preparation in the context of fair classification but also offer concrete, empirically grounded recommendations for practitioners. Our work lays the foundation for more informed pipeline design, providing a flexible, modular framework that can be readily extended to accommodate emerging data preparation techniques and new evaluation metrics.Diese Arbeit untersucht die entscheidende Rolle der Datenvorbereitung für die Vorhersageleistung und Fairness von binären Klassifikationsmodellen. Da Qualität und Zusammensetzung der Trainingsdaten das Modellverhalten maßgeblich beeinflussen, insbesondere im Hinblick auf eingebettete Verzerrungen, ist es entscheidend, dass Trainingsdaten sowohl akkurat als auch fair sind, um vertrauenswürdige maschinelle Lernsysteme zu entwickeln. Zu diesem Zweck erweitern wir eine bestehende Datenverarbeitungspipeline erheblich, indem wir deren Datenvorbereitungsphase durch die Integration von sechzehn zusätzlichen Methoden in fünf verschiedenen Komponenten umfassend ausbauen. Diese Erweiterung ermöglicht eine gründlichere Bewertung des Zusammenspiels zwischen Datenvorbereitung, Vorhersagegenauigkeit und algorithmischer Fairness.
Unsere empirische Studie verwendet eine Vielzahl von Klassifikatoren und Bewertungsmetriken, darunter mehrere neu entwickelte Maße, die speziell darauf ausgelegt sind, die subtilen Auswirkungen der Datenvorbereitung auf Modellergebnisse zu erfassen. Die Analyse umfasst sowohl reale als auch synthetische Datensätze und bietet damit eine solide Grundlage für unsere Erkenntnisse. Zu den zentralen Einsichten zählt die Beobachtung, dass eine bloße Erhöhung der Anzahl von Datenvorbereitungskomponenten nicht zwangsläufig zu einer Verbesserung der Modellleistung führt. Vielmehr hängen optimale Ergebnisse oft von sorgfältig ausgewählten Methoden und deren Reihenfolge ab, wobei einige Komponenten starke Positionsabhängigkeiten aufweisen. Zusätzlich bestätigen unsere Ergebnisse den vielfach dokumentierten Zielkonflikt zwischen Fairness und Genauigkeit, zeigen jedoch auch, dass es möglich ist, Konfigurationen zu identifizieren, bei denen beide Aspekte gleichzeitig verbessert werden können.
Diese Erkenntnisse vertiefen nicht nur unser Verständnis der Datenvorbereitung im Kontext fairer Klassifikation, sondern bieten Praktikern konkrete, empirisch fundierte Empfehlungen. Unsere Arbeit legt somit die Grundlage für ein besser informiertes Pipeline-Design und stellt einen flexiblen, modularen Rahmen bereit, der leicht erweitert werden kann, um zukünftige Datenvorbereitungstechniken und neue Bewertungsmetriken zu integrieren
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Full text link“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
Full text linkWe 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
Full text linkWe 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
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
Author Under Sail The Imagination of Jack London, 1893-1902
No full textIn Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Intro -- Title Page -- Copyright Page -- Dedication -- Contents -- Acknowledgments -- Introduction -- 1. Spirit Truth -- 2. From Absorption to Theatricality and Back Again -- 3. "I Will Build a New Present" -- 4. Sons as Authors -- 5. Fathers as Publishers -- 6. The Daughter as Author -- 7. Lovers as Authors -- 8. At Sea with the Family -- 9. Yellow News, Yellow Stories -- 10. The Return Home -- Notes -- Bibliography -- Index -- About Jay WilliamsIn Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Description based on publisher supplied metadata and other sources.Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, YYYY. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries
- …
