152 research outputs found

    MVMR-FS : Non-parametric feature selection algorithm based on Maximum inter-class Variation and Minimum Redundancy

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    How to accurately measure the relevance and redundancy of features is an age-old challenge in the field of feature selection. However, existing filter-based feature selection methods cannot directly measure redundancy for continuous data. In addition, most methods rely on manually specifying the number of features, which may introduce errors in the absence of expert knowledge. In this paper, we propose a non-parametric feature selection algorithm based on maximum inter-class variation and minimum redundancy, abbreviated as MVMR-FS. We first introduce supervised and unsupervised kernel density estimation on the features to capture their similarities and differences in inter-class and overall distributions. Subsequently, we present the criteria for maximum inter-class variation and minimum redundancy (MVMR), wherein the inter-class probability distributions are employed to reflect feature relevance and the distances between overall probability distributions are used to quantify redundancy. Finally, we employ an AGA to search for the feature subset that minimizes the MVMR. Compared with ten state-of-the-art methods, MVMR-FS achieves the highest average accuracy and improves the accuracy by 5% to 11%

    LIPIcs, Volume 261, ICALP 2023, Complete Volume

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    LIPIcs, Volume 261, ICALP 2023, Complete Volum

    Finding Optimal Diverse Feature Sets with Alternative Feature Selection

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    Feature selection is popular for obtaining small, interpretable, yet highly accurate prediction models. Conventional feature-selection methods typically yield one feature set only, which might not suffice in some scenarios. For example, users might be interested in finding alternative feature sets with similar prediction quality, offering different explanations of the data. In this article, we introduce alternative feature selection and formalize it as an optimization problem. In particular, we define alternatives via constraints and enable users to control the number and dissimilarity of alternatives. Next, we analyze the complexity of this optimization problem and show NP-hardness. Further, we discuss how to integrate conventional feature-selection methods as objectives. Finally, we evaluate alternative feature selection with 30 classification datasets. We observe that alternative feature sets may indeed have high prediction quality, and we analyze several factors influencing this outcome

    Finding Optimal Diverse Feature Sets with Alternative Feature Selection

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    Feature selection is popular for obtaining small, interpretable, yet highly accurate prediction models. Conventional feature-selection methods typically yield one feature set only, which might not suffice in some scenarios. For example, users might be interested in finding alternative feature sets with similar prediction quality, offering different explanations of the data. In this article, we introduce alternative feature selection and formalize it as an optimization problem. In particular, we define alternatives via constraints and enable users to control the number and dissimilarity of alternatives. Next, we analyze the complexity of this optimization problem and show NP-hardness. Further, we discuss how to integrate conventional feature-selection methods as objectives. Finally, we evaluate alternative feature selection with 30 classification datasets. We observe that alternative feature sets may indeed have high prediction quality, and we analyze several factors influencing this outcome

    Z-Numbers-Based Approach to Hotel Service Quality Assessment

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    In this study, we are analyzing the possibility of using Z-numbers for measuring the service quality and decision-making for quality improvement in the hotel industry. Techniques used for these purposes are based on consumer evalu- ations - expectations and perceptions. As a rule, these evaluations are expressed in crisp numbers (Likert scale) or fuzzy estimates. However, descriptions of the respondent opinions based on crisp or fuzzy numbers formalism not in all cases are relevant. The existing methods do not take into account the degree of con- fidence of respondents in their assessments. A fuzzy approach better describes the uncertainties associated with human perceptions and expectations. Linguis- tic values are more acceptable than crisp numbers. To consider the subjective natures of both service quality estimates and confidence degree in them, the two- component Z-numbers Z = (A, B) were used. Z-numbers express more adequately the opinion of consumers. The proposed and computationally efficient approach (Z-SERVQUAL, Z-IPA) allows to determine the quality of services and iden- tify the factors that required improvement and the areas for further development. The suggested method was applied to evaluate the service quality in small and medium-sized hotels in Turkey and Azerbaijan, illustrated by the example

    De l'apprentissage faiblement supervisé au catalogage en ligne

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    Applied mathematics and machine computations have raised a lot of hope since the recent success of supervised learning. Many practitioners in industries have been trying to switch from their old paradigms to machine learning. Interestingly, those data scientists spend more time scrapping, annotating and cleaning data than fine-tuning models. This thesis is motivated by the following question: can we derive a more generic framework than the one of supervised learning in order to learn from clutter data? This question is approached through the lens of weakly supervised learning, assuming that the bottleneck of data collection lies in annotation. We model weak supervision as giving, rather than a unique target, a set of target candidates. We argue that one should look for an “optimistic” function that matches most of the observations. This allows us to derive a principle to disambiguate partial labels. We also discuss the advantage to incorporate unsupervised learning techniques into our framework, in particular manifold regularization approached through diffusion techniques, for which we derived a new algorithm that scales better with input dimension then the baseline method. Finally, we switch from passive to active weakly supervised learning, introducing the “active labeling” framework, in which a practitioner can query weak information about chosen data. Among others, we leverage the fact that one does not need full information to access stochastic gradients and perform stochastic gradient descent.Les mathĂ©matiques appliquĂ©es et le calcul nourrissent beaucoup d’espoirs Ă  la suite des succĂšs rĂ©cents de l’apprentissage supervisĂ©. Dans l’industrie, beaucoup d’ingĂ©nieurs cherchent Ă  remplacer leurs anciens paradigmes de pensĂ©e par l’apprentissage machine. Étonnamment, ces ingĂ©nieurs passent plus de temps Ă  collecter, annoter et nettoyer des donnĂ©es qu’à raffiner des modĂšles. Ce phĂ©nomĂšne motive la problĂ©matique de cette thĂšse: peut-on dĂ©finir un cadre thĂ©orique plus gĂ©nĂ©ral que l’apprentissage supervisĂ© pour apprendre grĂące Ă  des donnĂ©es hĂ©tĂ©rogĂšnes? Cette question est abordĂ©e via le concept de supervision faible, faisant l’hypothĂšse que le problĂšme que posent les donnĂ©es est leur annotation. On modĂ©lise la supervision faible comme l’accĂšs, pour une entrĂ©e donnĂ©e, non pas d’une sortie claire, mais d’un ensemble de sorties potentielles. On plaide pour l’adoption d’une perspective « optimiste » et l’apprentissage d’une fonction qui vĂ©rifie la plupart des observations. Cette perspective nous permet de dĂ©finir un principe pour lever l’ambiguĂŻtĂ© des informations faibles. On discute Ă©galement de l’importance d’incorporer des techniques sans supervision d’apprĂ©hension des donnĂ©es d’entrĂ©e dans notre thĂ©orie, en particulier de comprĂ©hension de la variĂ©tĂ© sous-jacente via des techniques de diffusion, pour lesquelles on propose un algorithme rĂ©aliste afin d’éviter le flĂ©au de la dimension, Ă  l’inverse de ce qui existait jusqu’alors. Enfin, nous nous attaquons Ă  la question de collecte active d’informations faibles, dĂ©finissant le problĂšme de « catalogage en ligne », oĂč un intendant doit acquĂ©rir une maximum d’informations fiables sur ses donnĂ©es sous une contrainte de budget. Entre autres, nous tirons parti du fait que pour obtenir un gradient stochastique et effectuer une descente de gradient, il n’y a pas besoin de supervision totale

    Methods in Contemporary Linguistics

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    The present volume is a broad overview of methods and methodologies in linguistics, illustrated with examples from concrete research. It collects insights gained from a broad range of linguistic sub-disciplines, ranging from core disciplines to topics in cross-linguistic and language-internal diversity or to contributions towards language, space and society. Given its critical and innovative nature, the volume is a valuable source for students and researchers of a broad range of linguistic interests

    Essays in Behavioral Economics and Microeconomic Theory

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    Kapitel 1: Im Rahmen des Erwartungsnutzenmodells leite ich ein theoretisches Modell von choice bracketing aus zwei verhaltensökonomischen Axiomen ab. Das erste etabliert einen direkten Zusammenhang zwischen narrow bracketing und correlation neglect. Das zweite identifiziert den Referenzpunkt als den Ort, an dem broad und narrow PrĂ€ferenzen miteinander verbunden sind. In meinem Modell ist der narrow bracketer durch die UnfĂ€higkeit, VerĂ€nderungen vom Referenzpunkt in unterschiedlichen Dimensionen gleichzeitig zu verarbeiten, charakterisiert. Kapitel 2: Warum geben Menschen, wenn man sie fragt, prĂ€ferieren aber, nicht gefragt zu werden, und nehmen sogar, wenn sich die Gelegenheit ergibt? Wir zeigen, dass Axiome wie SeparabilitĂ€t, narrow bracketing, und scaling invariance diese scheinbar widersprĂŒchlichen Beobachtungen vorhersagen. Insbesondere implizieren diese Axiome, dass die Interdependenz von PrĂ€ferenzen (“Altruismus”) ein Ergebnis des Interesses fĂŒr das Wohlbefinden anderer im Gegensatz zu ihren bloßen Auszahlungen ist. Hierbei wird das Wohlbefinden durch die referenzabhĂ€ngige Wertfunktion aus der Prospekttheorie erfasst. Kapitel 3: Wir untersuchen, wie sich fake news auf den Informationsfluss zwischen Nachrichtenportalen und  ökonomischen Agenten auswirkt. Wir erweitern das klassische cheaptalk- Modell um Unsicherheit ĂŒber die PrĂ€ferenzen des sender (Nachrichtenportal). Es gibt zwei Typen von Nachrichtenportalen. Ein fake-news-Portal möchte im Agenten unabhĂ€ngig vom wahren Zustand eine maximale Erwartung wecken. Ein legitimes Nachrichtenportal möchte die Wahrheit offenbaren. Wir zeigen, dass jedes informative perfekte Bayesianische Gleichgewicht durch einen Schwellenwert charakterisiert ist. WĂ€hrend der Agent alle ZustĂ€nde unter dem Schwellenwert unterscheiden kann, ist es ihm unmöglich, ZustĂ€nde ĂŒber dem Schwellenwert zu unterscheiden.Chapter 1: I derive a theoretical model of choice bracketing from two behavioral axioms in an expected utility framework. The first behavioral axiom establishes a direct link between narrow bracketing and correlation neglect. The second behavioral axiom identifies the reference point as the place where broad and narrow preferences are connected. In my model, the narrow bracketer is characterized by an inability to process changes from the reference point in different dimensions simultaneously. Chapter 2: Why do people give when asked, but prefer not to be asked, and even take when possible? We show that standard behavioral axioms including separability, narrow bracketing, and scaling invariance predict these seemingly inconsistent observations. Specifically, these axioms imply that interdependence of preferences (“altruism”) results from concerns for the welfare of others, as opposed to their mere payoffs, where individual welfares are captured by the reference-dependent value functions known from prospect theory. The resulting preferences are non-convex, which captures giving, sorting, and taking directly. Chapter 3: We present a theoretical model to investigate how the presence of fake news affects information transmission from media outlets to economic agents. In a standard cheap talk framework we introduce uncertainty about the sender’s (media outlet’s) preferences. There are two types of media outlets. A fake news outlet wants to push the agent’s belief to the maximum irrespective of the state of the world. A legitimate outlet wants to reveal the true state to the agent. We show that any informative perfect Bayesian equilibrium of our game is characterized by a threshold value. While the agent can perfectly separate amongst states below the threshold value, there is no separation amongst states above the threshold value. We determine the unique most informative threshold value for a general class of equilibria

    Legal methods for resolving apparent conflicts between fundamental rights

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    The subject of this thesis are apparent conflicts between fundamental rights, which represent one of the most important problems contemporary legal systems are faced with. More specifically, this thesis presents and analyses different legal methods that have been suggested as answers to the problem. Contemporary constitutions usually contain provisions protecting certain fundamental rights, such as the right to life, the right to privacy, the right to freedom of expression, personality rights, the right to health, etc. The problem can arise when two (or more) provisions protecting fundamental rights are relevant to the specific situation. The question can then arise: should the behaviour be permitted or prohibited? Judges may then be faced with the situation of having to decide the case without any explicit or clear guidance on how to decide the case. In such situations, lex superior, lex posterior and lex specialis are usually inapplicable, because the provisions regulating fundamental rights are usually on the same hierarchical level, were enacted at the same time and no general – special relationship can be established between them. The problem is further complicated by the fact that the norms expressing fundamental rights are generally understood as legal principles, supposedly different from legal rules. These cases are commonly referred to and known in the literature as hard cases. In order to decide such cases and solve the problem we are faced with various legal methods have been proposed. These methods represent possible answers to the problem of the resolution of the apparent conflicts between fundamental rights. The term “apparent” is used, since there is a debate regarding the existence of “real” conflicts between fundamental rights. The objective of the thesis is to provide an answer to the research question: What are the legal methods of resolving apparent conflicts between fundamental rights and what are their merits in comparison to each other? In order to answer the research question, different legal methods that have been suggested as an answer to the problem of apparent conflicts between fundamental rights are presented, analysed and compared. In this way, the thesis aims to contribute to the understanding of the strengths and weaknesses of the different legal methods that have been proposed to solve the problem. To achieve this, the thesis is divided into three main chapters, each of which presents and analyses different legal methods on apparent conflicts between fundamental rights. In Chapter I and Chapter II, the main legal method proposed to resolve apparent conflicts between fundamental rights – judicial balancing – is presented and analysed. In Chapter III, alternative, non-balancing legal methods for resolving apparent conflicts between fundamental rights are presented and analysed. Chapter I presents and analyses Alexyan theory of judicial balancing, developed by Robert Alexy and further refined by his disciples Jan-Reinard Sieckmann, Martin Borowski and Matthias Klatt. Chapter II presents and analyses approaches from Aharon Barak, Manuel Atienza, JosĂ© Juan Moreso, Riccardo Guastini and Susan Lynn Hurley. In Chapter III, alternative, non-balancing legal methods for resolving apparent conflicts between fundamental rights are presented and analysed. The authors whose approaches are analysed and presented in this chapter are, in this order: Ronald Dworkin, Luigi Ferrajoli, Juan Antonio GarcĂ­a Amado, Lorenzo Zucca and Ruth Chang
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