Majority voting

Most research in text classification to date has used a “bag of words” representation in which each feature corresponds to a single word. This paper examines some alternative ways to represent text based on syntactic and semantic relationships between words (phrases, synonyms ...

Voting in uncontrolled environment either by post or by the Internet is about to be made generally available in many countries. The main purpose is to increase participation at times when the voter turnout is generally decreasing. Electronic voting both in or outside controlled environment offers advantages in producing fast and reliable results and long term cost savings in the conduct of elections. A number of problems relating to security, reliability and general trust can be solved by Internet voting, once an infrastructure for voter identification is in place. However, neither postal votes nor Internet votes can guarantee that the vote is cast in secrecy without intimidation or pressure. Even without the most serious violations to a free vote, the pattern of voting will change and the concept of voting being a strictly personal and secret act is likely to be weakened over time. There are few reasons to doubt that the introduction of voting by Internet once generally available w...

Never has voting been more important in corporate law. With greater activism among shareholders and the shift from plurality to majority voting for directors, the number of close votes is rising. But is the basic technology of corporate voting adequate to the task? In this Article, we first examine the incredibly complicated system of US corporate voting, a complexity that is driven by the underlying custodial ownership structure, by dispersed ownership and large trading volumes, and by the rise in short-selling and derivatives. We identify three ways in which things predictably go wrong: pathologies of complexity; pathologies of ownership; and pathologies of misalignment of interests. We then discuss the current legal treatment of these pathologies and consider a variety of directions for reform, ranging from incremental modifications to fundamental redesign. We show that, absent a fundamental reconstruction of the ownership structure, the existing system will continue to be noisy,...

Most research in text classification has used the “bag of words ” representation of text. This paper examines some alternative ways to represent text based on syntactic and semantic relationships between words (phrases, synonyms and hypernyms). We describe the new representations and try to justify our suspicions that they could have improved the performance of a rule-based learner. The representations are evaluated using the RIPPER rule-based learner on the Reuters-21578 and DigiTrad test corpora, but on their own the new representations are not found to produce a significant performance improvement. Finally, we try combining classifiers based on different representations using a majority voting technique. This step does produce some performance improvement on both test collections. In general, our work supports the emerging consensus in the information retrieval community that more sophisticated Natural Language Processing techniques need to be developed before better text represe...

The N-Modular Redundancy (NMR) architecture has shown to perform fault-masking with acceptable cost and performance. The restriction to the majority voting imposed by many of its implementation models often discourages its use in real-time applications with sensors' data. Its implementation in real applications also exhibits time overhead, and synchronization problems beside the increase in hardware cost it involves. This paper

Abstract— Gender classification problem is an active area of research; recently it had attracted many researchers. This study presents an efficient gender classification technique. Weighted Majority Voting (WMV) is the most popular technique used to combine individual ...

In this paper, we investigate the possible externalities due to a minimum wage policy in an integrated market. We examine both descriptive and normative perspectives. We consider two identical countries for whom comparative advantage is attributed to different social policies. Each ...

A script independent recognition scheme for handwritten characters using multiple MLP classifiers and wavelet transform-based multiresolution pixel features is presented. We studied four different approaches for combination of multiple MLP classifiers and observed that a weighted majority voting approach provided the best recognition performance. Also, a thumb rule for the selection of network architecture has been obtained and a dynamic strategy for selection of training samples has been studied. The dynamic training set ...

Proactive contact campaigns play a growing role in modern contact centers. Their traditional usage as a telemarketing tool now is widely extended to different types of service notifications. In this paper we describe the most common model of a proactive telephone ...

ABSTRACT One problem in the field of machine learning is that the performance on the training and validation sets lack robustness when applied in real-life situations. Recent advances in ensemble methods have demonstrated that robust behavior can be improved by combining a large number of weak classifiers. The key insight of this paper is that the performance enhancement due to combining multiple classifiers is considerably greater in multi-category situations than in binary classifications, as long as their errors are conditionally independent. This paper provides some experimental and theoretical analysis of the performance using majority vote, paying special attention to the effect of several parameters that include the number of combined classifiers, weakness of the combined classifiers and the number of classes. These insights can provide guidance for the analysis and design of multi-classifier systems.

The problem of the aggregation of consistent individual judgments on logically interconnected propositions into a collective judgment on the same propositions has recently drawn much attention. The difficulty lies in the fact that a seemingly reasonable aggregation procedure, such as propositionwise majority voting, cannot ensure an equally consistent collective outcome. The literature on judgment aggregation refers to such dilemmas as the discursive paradox. So far, three procedures have been proposed to overcome the paradox: the premise-based and conclusion-based procedures on the one hand, and the merging approach on the other hand. In this paper we assume that the decision which the group is trying to reach is factually right or wrong. Hence, the question is how good the merging approach is in tracking the truth, and how it compares with the premise-based and conclusion-based procedures.

In this paper three different approaches for person verification and identification, ie by means of fingerprints, face and voice recognition, are studied. Face recognition uses parts-based representation methods and a manifold learning approach. The assessment criterion is recognition accuracy. The techniques under investigation are: a) Local Non-negative Matrix Factorization (LNMF); b) Independent Components Analysis (ICA); c) NMF with sparse constraints (NMFsc); d) Locality Preserving Projections (Laplacianfaces). ...

Abstract— Gender classification problem is an active area of research; recently it had attracted many researchers. This study presents an efficient gender classification technique. Weighted Majority Voting (WMV) is the most popular technique used to combine individual ...

Segmentation of optical images may be obtained through algorithms based on image prior models that exploit the spatial dependencies of land covers. In synthetic aperture radar (SAR) images, speckle conceals such spatial dependencies and segmentation algorithms suitable for optical images may become ineffective. Textural features may be used to emphasize spatial dependencies in the data and hence to improve segmentation. Once segmentation has been accomplished, a number of shapes is available. In this paper, the problem is tackled through the joint use of information-theoretic (IT) SAR features, of a segmentation algorithm based on tree structured Markov random fields (TS-MRFs), and of object-oriented classification achieved through learning vector quantization (LVQ). The proposed system works with one or more coregistered images, not necessarily all SAR, and one or more spatial maps of pixel features derived from each input image. A unique partition into connected regions, or segments, is achieved from the plurality of input channels, either images or feature maps. From each segment, representing a shape, geometric, radiometric, and textural parameters are extracted and fed to an LVQ classifier, trained through a partial reference ground truth (GT) of the scene. Classification results on a textured SAR image of a city and its surroundings validate the proposed object-oriented approach. Good performances can be achieved with small sizes of training sets, but they can be improved by using a decision fusion through majority voting (MV) of the outcomes of several experiments.

The thesis presented here analyzes the role of the less developed countries in the environmental issues in the United Nations, evaluates their influence, and analyzes the determinants of this influence. Our study assumes certain goal orientations of spokesmen for the less developed countries. These goal orientations are derived from the underdeveloped condition of most of these countries and their continuing political and economic dependence. They attempt to reduce this dependence through demands for radical transformations in the international political economy. This is done through negotiations with spokesmen for the developed countries. The attainment of their objectives constitutes an exercise of influence over their counterparts from the developed countries. The outcomes themselves, for our study, are less important than the interactions, styles,and conversion of political resources into influence. Therefore, it is on the dynamics of the North-South set of international relatio...

This paper defines a measure of bargaining uncertainty that quantifies Roth's concept of strategic risk. It shows how this measure can be used for checking reliability of the Shapley value in cost allocation problems and in the theory of competitive equilibrium. Salient properties of the new measure are investigated and illustrated by examples of majority voting and market games and by a cost allocation problem from epidemiology.

In this paper, we analyze the equilibrium on the market for schooling where both public and private schools coexist and where individuals are differentiated by income and ability. We introduce a non linear in means model of peer effect by shedding the light on the fact that school quality is not solely dependent on mean ability but also on the dispersion of abilities. We study the distribution of students across sectors while examining the conditions for the existence of a majority voting equilibrium in the context of non single peaked preferences. Finally, we examine the presence of a hierarchy of school qualities. In the paper we shed the light on equity problems related to the access to educational quality while analyzing the functioning of the educational system.

Web spam can significantly deteriorate the quality of search engine results. Thus there is a large incentive for commercial search engines to detect spam pages efficiently and accurately. In this paper we present a spam detection system that combines link-based and content-based features, and uses the topology of the Web graph by exploiting the link dependencies among the Web pages. We find that linked hosts tend to belong to the same class: either both are spam or both are non-spam. We demonstrate three methods of ...