Search results for "Decision rule"
showing 10 items of 38 documents
Opportunity costs resulting from scramble competition within the choosy sex severely impair mate choosiness.
2016
12 pages; International audience; Studies on mate choice mainly focus on the evolution of signals that would maximize the probability of finding a good-quality partner. Most models of sexual selection rely on the implicit assumption that individuals can freely compare and spot the best mates in a heterogeneous population. Comparatively few studies have investigated the consequences of the mate-sampling process. Several sampling strategies have been studied from theoretical or experimental perspectives. They belong to two families of decision rules: best-of-n strategies (individuals sample n partners before choosing the best one within this pool) or threshold strategies (individuals sequenti…
Female mate choice in convict cichlids is transitive and consistent with a self-referent directional preference
2013
10 pages; International audience; INTRODUCTION: One of the most important decisions that an animal has to make in its life is choosing a mate. Although most studies in sexual selection assume that mate choice is rational, this assumption has not been tested seriously. A crucial component of rationality is that animals exhibit transitive choices: if an individual prefers option A over B, and B over C, then it also prefers A over C. RESULTS: We assessed transitivity in mate choice: 40 female convict cichlids had to make a series of binary choices between males of varying size. Ninety percent of females showed transitive choices. The mean preference index was significantly higher when a female…
Assortative mating by size without a size-based preference: the female-sooner norm as a mate-guarding criterion.
2013
7 pages; International audience; The study of size-assortative mating, or homogamy, is of great importance in speciation and sexual selection. However, the proximate mechanisms that lead to such patterns are poorly understood. Homogamy is often thought to come from a directional preference for larger mates. However, many constraints affect mating preferences and understanding the causes of size assortment requires a precise evaluation of the pair formation mechanism. Mate-guarding crustaceans are a model group for the study of homogamy. Males guard females until moult and reproduction. They are also unable to hold a female during their own moult and tend to pair with females closer to moult…
A Novel Intelligent Technique of Invariant Statistical Embedding and Averaging via Pivotal Quantities for Optimization or Improvement of Statistical …
2020
In the present paper, for intelligent constructing efficient (optimal, uniformly non-dominated, unbiased, improved) statistical decisions under parametric uncertainty, a new technique of invariant embedding of sample statistics in a decision criterion and averaging this criterion over pivots’ probability distributions is proposed. This technique represents a simple and computationally attractive statistical method based on the constructive use of the invariance principle in mathematical statistics. Unlike the Bayesian approach, the technique of invariant statistical embedding and averaging via pivotal quantities (ISE&APQ) is independent of the choice of priors and represents a novelty i…
Defining classifier regions for WSD ensembles using word space features
2006
Based on recent evaluation of word sense disambiguation (WSD) systems [10], disambiguation methods have reached a standstill. In [10] we showed that it is possible to predict the best system for target word using word features and that using this 'optimal ensembling method' more accurate WSD ensembles can be built (3-5% over Senseval state of the art systems with the same amount of possible potential remaining). In the interest of developing if more accurate ensembles, w e here define the strong regions for three popular and effective classifiers used for WSD task (Naive Bayes – NB, Support Vector Machine – SVM, Decision Rules – D) using word features (word grain, amount of positive and neg…
Predictive model to identify the risk of losing protective sensibility of the foot in patients with diabetes mellitus
2019
Diabetic neuropathy is defined as the presence of symptoms and signs of peripheral nerve dysfunction in diabetics. The aim of this study is to develop a predictive logistic model to identify the risk of losing protective sensitivity in the foot. This descriptive cross‐sectional study included 111 patients diagnosed with diabetes mellitus. Participants completed a questionnaire designed to evaluate neuropathic symptoms, and multivariate analysis was subsequently performed to identify an optimal predictive model. The explanatory capacity was evaluated by calculating the R (2) coefficient of Nagelkerke. Predictive capacity was evaluated by calculating sensitivity, specificity, and estimation o…
Elements of Significance Testing with Equivalence Problems
1991
AbstractThe paper outlines an approach to the general methodological problem of equivalence assessment which is based on the classical theory of testing statistical hypotheses. Within this frame of reference it is natural to search for decision rules satisfying the same criteria of optimality which are customarily applied in deriving solutions to one- and two-sided testing problems. For three standard situations very frequently encountered in medical applications of statistics, a concise account of such an optimal test for equivalence is presented. It is pointed out that tests based on the well-known principle of confidence interval inclusion are valid in the sense 1 of guaranteeing the pre…
Constructing Interpretable Classifiers to Diagnose Gastric Cancer Based on Breath Tests
2017
Quick, inexpensive and accurate diagnosis of gastric cancer is a necessity, but at this moment the available methods do not hold up. One of the most promising possibilities is breath test analysis, which is quick, relatively inexpensive and comfortable to the person tested. However, this method has not yet been well explored. Therefore in this article the authors propose using transparent classification models to explain diagnostic patterns and knowledge, which is acquired in the process. The models are induced using decision tree classification algorithms and RIPPER algorithm for decision rule induction. The accuracy of these models is compared to neural network accuracy.
A computer program suitable for analysis of choice of categories in biomedical data recognition problems.
1980
The optimum choice of categories in problems of medical data recognition is governed by the choice of categories, the selection of appropriate features, and by the choice of a loss function. Under these circumstances it is often difficult to find out the suitable classification scheme. The computer program described here serves for the design of the optimum recognition procedure. The Bayes rule is used as decision rule. A criterion for the comparison of different choice of categories is given. The program can be performed after estimation of the underlying prior probabilities and the conditional densities obtained from a training set, and before testing the decision rule with real data.
SVM approximation for real-time image segmentation by using an improved hyperrectangles-based method
2003
A real-time implementation of an approximation of the support vector machine (SVM) decision rule is proposed. This method is based on an improvement of a supervised classification method using hyperrectangles, which is useful for real-time image segmentation. The final decision combines the accuracy of the SVM learning algorithm and the speed of a hyperrectangles-based method. We review the principles of the classification methods and we evaluate the hardware implementation cost of each method. We present the combination algorithm, which consists of rejecting ambiguities in the learning set using SVM decision, before using the learning step of the hyperrectangles-based method. We present re…