1,721,020 research outputs found
A different class-assignment rule to build classification trees for ordinal outcomes
No full textIntroduction. Classification and regression trees (CART) are binary recursive partitioning methods designed to construct prediction models for categorical (classification) or continuous (regression) variables from data. One of the key elements of classification trees is the assignment rule of each terminal node (leaf) to a class outcome.
Objectives. Evaluating the performance of the ‘median trees’, built with a novel approach to class assignment, compared to the ‘modal trees’, built with the majority rule, when an ordinal outcome (y) is assumed.
Materials and Methods. Modal trees were estimated using the modal class among the observations that fall into each leaf to assign y-classes, whereas median trees were estimated through the median class. According to the assignment rule adopted, the predicted power of the trees was evaluated by two different approaches: modal trees minimized the total number of errors; median trees minimized the sum of absolute distances between predicted class and observed class. Tree performances were evaluated through the gamma statistic, measuring the association between observed and predicted classes. Three real datasets with different number of y-levels (from four to six) were analyzed. Each dataset was divided into a training set, for building the trees, and a testing set, for evaluating prediction accuracy. A resampling of the testing set (n=30) was carried out to derive robust estimates. Binomial test and paired t-test were used to compare the significance of differences between tree performances.
Results. Median tree performances were significantly better than modal ones with five and six y-classes. Significant differences were not observed with four levels of the outcome. No matter of the number of y-classes, median trees showed a simpler structure (smaller number of leaves) than modal ones.
Conclusion. Median trees showed a better performance than modal trees with an increasing number of y-levels and generally provided a simpler structure which allows an easier interpretation of the patterns and connections among groups of interest
rpartScore: Classification trees for ordinal responses
No full textThis package contains functions that allow to build classification trees for ordinal responses within the CART framework. The trees are grown using the Generalized Gini impurity function, where the misclassification costs are given by the absolute or squared differences in scores assigned to the categories of the response. Pruning is based on the total misclassification rate or on the total misclassification cost
Classification Trees for Ordinal Responses in R: The rpartScore Package
Full text linkThis paper introduces rpartScore (Galimberti, Soffritti, and Di Maso 2012), a new R package for building classification trees for ordinal responses, that can be employed whenever a set of scores is assigned to the ordered categories of the response. This package has been created to overcome some problems that produced unexpected results from the package rpartOrdinal (Archer 2010). Explanations for the causes of these unexpected results are provided. The main functionalities of rpartScore are described, and its use is illustrated through some examples
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
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