Using Sensitivity as a Method for Ranking the Test Cases Classified by Binary Decision Trees

Usually, data mining projects that are based on decision trees for classifying test cases will use the probabilities provided by these decision trees for ranking classified test cases. We have a need for a better method for ranking test cases that have already been classified by a binary decision tree because these probabilities are not always accurate and reliable enough. A reason for this is that the probability estimates computed by existing decision tree algorithms are always the same for all the different cases in a particular leaf of the decision tree. This is only one reason why the probability estimates given by decision tree algorithms can not be used as an accurate means of deciding if a test case has been correctly classified. Isabelle Alvarez has proposed a new method that could be used to rank the test cases that were classified by a binary decision tree [Alvarez, 2004]. In this paper we will give the results of a comparison of different ranking methods that are based on the probability estimate, the sensitivity of a particular case or both.

Microcapsules of a Casein Hydrolysate: Production, Characterization, and Application in Protein Bars

The aim of this work was to encapsulate a casein hydrolysate by spray drying using maltodextrins (DE 10 and 20) as wall materials and to evaluate the efficiency of the microencapsulation in attenuating the bitter taste of the hydrolysate using protein bars as the model system. Microcapsules were evaluated for morphology (SEM), particle size, hygroscopicity, solubility, thermal behavior (DSC), and bitter taste with a trained sensory panel by a paired comparison test (nonencapsulated samples vs. encapsulated samples). Bars were prepared with the addition of 3% casein hydrolysate at free or both encapsulated forms, and were then evaluated for their moisture, water activity (a(w)) and for their bitter taste by a ranking test. Microcapsules were of the matrix type, having continuous surfaces with no apparent porosity for both coatings. Both encapsulated casein hydrolysates had similar hygroscopicity, and lower values than free encapsulated hydrolysates. The degree of hydrolysis of the maltodextrin influenced only the particle size and T(g). The sensory panel considered the protein bars produced with both encapsulated materials less bitter (p < 0.05) than those produced with the free casein hydrolysates. Microencapsulation by spray drying with maltodextrin DE 10 and 20 was successful to attenuate the bitter taste and the hygroscopicity of casein hydrolysates.

A Parametric Test of Perfect Ranking in Balanced Ranked Set Sampling

Many techniques based on data which are drawn by Ranked Set Sampling (RSS) scheme assume that the ranking of observations is perfect. Therefore it is essential to develop some methods for testing this assumption. In this article, we propose a parametric location-scale free test for assessing the assumption of perfect ranking. The results of a simulation study in two special cases of normal and exponential distributions indicate that the proposed test performs well in comparison with its leading competitors.

Bottom-up review : analysis of DOD war game to test key assumptions : report to the Chairman and Ranking Minority Member, Committee on National Security, House of Representatives /

"B-272119"--P. 1.

Structured Learning for Non-Smooth Ranking losses

Learning to rank from relevance judgment is an active research area. Itemwise score regression, pairwise preference satisfaction, and listwise structured learning are the major techniques in use. Listwise structured learning has been applied recently to optimize important non-decomposable ranking criteria like AUC (area under ROC curve) and MAP(mean average precision). We propose new, almost-lineartime algorithms to optimize for two other criteria widely used to evaluate search systems: MRR (mean reciprocal rank) and NDCG (normalized discounted cumulative gain)in the max-margin structured learning framework. We also demonstrate that, for different ranking criteria, one may need to use different feature maps. Search applications should not be optimized in favor of a single criterion, because they need to cater to a variety of queries. E.g., MRR is best for navigational queries, while NDCG is best for informational queries. A key contribution of this paper is to fold multiple ranking loss functions into a multi-criteria max-margin optimization.The result is a single, robust ranking model that is close to the best accuracy of learners trained on individual criteria. In fact, experiments over the popular LETOR and TREC data sets show that, contrary to conventional wisdom, a test criterion is often not best served by training with the same individual criterion.

Extending Distance-based Ranking Models In Estimation of Distribution Algorithms

Recently, probability models on rankings have been proposed in the field of estimation of distribution algorithms in order to solve permutation-based combinatorial optimisation problems. Particularly, distance-based ranking models, such as Mallows and Generalized Mallows under the Kendall’s-t distance, have demonstrated their validity when solving this type of problems. Nevertheless, there are still many trends that deserve further study. In this paper, we extend the use of distance-based ranking models in the framework of EDAs by introducing new distance metrics such as Cayley and Ulam. In order to analyse the performance of the Mallows and Generalized Mallows EDAs under the Kendall, Cayley and Ulam distances, we run them on a benchmark of 120 instances from four well known permutation problems. The conducted experiments showed that there is not just one metric that performs the best in all the problems. However, the statistical test pointed out that Mallows-Ulam EDA is the most stable algorithm among the studied proposals.

Divulgación on-line de los códigos de buen gobierno en las IES y su determinación para el posicionamiento en el ranking QS

Dado el interés que se presenta con los temas de gobierno corporativo, este trabajo busca describir si la divulgación on-line de los contenidos de los códigos de buen gobierno, es determinante en el posicionamiento que tienen las Instituciones de Educación Superior (IES) en el ranking QS. Partiendo de una muestra de 20 IES, se recolectaron un conjunto de datos dicotómicos para 30 variables independientes y se relacionaron con la variable dependiente denominada posicionamiento en el ranking. A partir de lo anterior, se elaboró un trabajo descriptivo y correlacional con el fin de probar las hipótesis de investigación. Este estudio reveló que la divulgación on-line de los contenidos de los códigos de buen gobierno en las IES, no es determinante para el posicionamiento en el ranking QS.

Evaluation of a novel kit (TF-test) for the diagnosis of intestinal parasitic infections

Intestinal parasitic infections are currently a source of concern for Public Health agencies in developing and developed countries. Since three ovum-and-parasite stool examinations have been demonstrated to provide sensitive results, we designed a practical and economical kit (TF-Test) that is now commercially available (Immunoassay Com. Ind. Ltda., S (a) over tildeo Paulo, Brazil). This kit allows the separate collection of three fecal specimens into a preservative solution. The specimens are then pooled, double-filtered, and concentrated by a single rapid centrifugation process. The TF-Test was evaluated in four different laboratories in a study using 1,102 outpatients and individuals living in an endemic area for enteroparasitosis. The overall sensitivity found using the TF-Test (86.2-97.8%) was significantly higher (P<0.01) than the sensitivity of conventional techniques such as the Coprotest (NIL Comercio Exterior Ltda, São Paulo, Brazil) and the combination of Lutz/Hoffman, Faust, and Rugai techniques (De Carli, Diagnostico Laboratorial das Parasitoses Humanas. Metodos e Tecnicas, 1994), which ranged from 48.3% to 75.9%. When the above combined three specimen technique was repeated with three specimens collected on different days, its sensitivity became similar (P > 0.01) to that of the TF-Test. The kappa index values of agreement for the TF-Test were consistent (P < 0.01), being higher and ranking in a better position than conventional techniques. The high sensitivity, cost/benefit ratio, and practical aspects demonstrate that the TF-Test is suitable for individual diagnosis, epidemiological inquiries, or evaluation of chemotherapy in treated communities. (C) 2004 Wiley-Liss, Inc.

The effects of anxiety on visual search, movement kinematics, and performance in table tennis: A test of Eysenck and Calvo's processing efficiency theory

Processing efficiency theory predicts that anxiety reduces the processing capacity of working memory and has detrimental effects on performance. When tasks place little demand on working memory, the negative effects of anxiety can be avoided by increasing effort. Although performance efficiency decreases, there is no change in performance effectiveness. When tasks impose a heavy demand on working memory, however, anxiety leads to decrements in efficiency and effectiveness. These presumptions were tested using a modified table tennis task that placed low (LWM) and high (HWM) demands on working memory. Cognitive anxiety was manipulated through a competitive ranking structure and prize money. Participants' accuracy in hitting concentric circle targets in predetermined sequences was taken as a measure of performance effectiveness, while probe reaction time (PRT), perceived mental effort (RSME), visual search data, and arm kinematics were recorded as measures of efficiency. Anxiety had a negative effect on performance effectiveness in both LWM and HWM tasks. There was an increase in frequency of gaze and in PRT and RSME values in both tasks under high vs. low anxiety conditions, implying decrements in performance efficiency. However, participants spent more time tracking the ball in the HWM task and employed a shorter tau margin when anxious. Although anxiety impaired performance effectiveness and efficiency, decrements in efficiency were more pronounced in the HWM task than in the LWM task, providing support for processing efficiency theory.

Skin test and tick immune status in susceptible and resistant cattle in Brazil

A cutaneous hypersensitivity test (CHT) was used to correlate host resistance to ticks and type of reaction elicited to unfed larval extract-ULE of the cattle tick Boophilus microplus in European and Indian cattle. Twenty calves were separated into four groups of five animals each: naïve or preinfested Indian or European cattle. CHT was induced by intradermal inoculation of 0.1 ml of ULE cattle tick B. microplus (50 μg protein) in the calf ear. Ear thickness was measured using calipers before and 10 min, 1, 2, 6, 18, 24, 48, 72, 96, and 144 h postinoculation (PI). Preinfested European calves showed only an immediate type reaction with maximum response (75% increase in ear thickness) at 10 min PI. On the other hand, preinfested Indian calves presented an immediate response with maximum reaction (70% increase in ear thickness) between 10 min and one hour PI, and a delayed type reaction at 72 h PI (60% increase in ear thickness). These results point out the crucial role of the cellular immune response of cattle in the expression of resistance to cattle tick B. microplus. Skin test might be useful in the ranking of cattle according to the susceptibility/resistance to ticks.

A connection between two nonparametric tests for perfect ranking in balanced ranked set sampling

In this note, we show that an extension of a test for perfect ranking in a balanced ranked set sample given by Li and Balakrishnan (2008) to the multi-cycle case turns out to be equivalent to the test statistic proposed by Frey et al. (2007). This provides an alternative interpretation and motivation for their test statistic.

Using incomplete citation data for MEDLINE results ranking.

Information overload is a significant problem for modern medicine. Searching MEDLINE for common topics often retrieves more relevant documents than users can review. Therefore, we must identify documents that are not only relevant, but also important. Our system ranks articles using citation counts and the PageRank algorithm, incorporating data from the Science Citation Index. However, citation data is usually incomplete. Therefore, we explore the relationship between the quantity of citation information available to the system and the quality of the result ranking. Specifically, we test the ability of citation count and PageRank to identify "important articles" as defined by experts from large result sets with decreasing citation information. We found that PageRank performs better than simple citation counts, but both algorithms are surprisingly robust to information loss. We conclude that even an incomplete citation database is likely to be effective for importance ranking.

Using incomplete citation data for MEDLINE results ranking.

Information overload is a significant problem for modern medicine. Searching MEDLINE for common topics often retrieves more relevant documents than users can review. Therefore, we must identify documents that are not only relevant, but also important. Our system ranks articles using citation counts and the PageRank algorithm, incorporating data from the Science Citation Index. However, citation data is usually incomplete. Therefore, we explore the relationship between the quantity of citation information available to the system and the quality of the result ranking. Specifically, we test the ability of citation count and PageRank to identify "important articles" as defined by experts from large result sets with decreasing citation information. We found that PageRank performs better than simple citation counts, but both algorithms are surprisingly robust to information loss. We conclude that even an incomplete citation database is likely to be effective for importance ranking.