Search results for "Weighted distance"

showing 2 items of 2 documents

Weighted distance-based trees for ranking data

2017

Within the framework of preference rankings, the interest can lie in finding which predictors and which interactions are able to explain the observed preference structures, because preference decisions will usually depend on the characteristics of both the judges and the objects being judged. This work proposes the use of a univariate decision tree for ranking data based on the weighted distances for complete and incomplete rankings, and considers the area under the ROC curve both for pruning and model assessment. Two real and well-known datasets, the SUSHI preference data and the University ranking data, are used to display the performance of the methodology.

Statistics and ProbabilityDecision tree03 medical and health sciences0302 clinical medicine0504 sociology030225 pediatricsPreference dataStatisticsDecision treePruning (decision trees)University ranking dataDistance-based methodMathematicsWeighted distanceApplied Mathematics05 social sciencesUnivariate050401 social sciences methodsSUSHI dataComputer Science Applications1707 Computer Vision and Pattern RecognitionPreferenceComputer Science ApplicationsRankingRanking dataKemeny distanceSettore SECS-S/01 - StatisticaArea under the roc curve
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Weighted and unweighted distances based decision tree for ranking data

2018

Preference data represent a particular type of ranking data (widely used in sports, web search, social sciences), where a group of people gives their preferences over a set of alternatives. Within this framework, distance-based decision trees represent a non-parametric tool for identifying the profiles of subjects giving a similar ranking. This paper aims at detecting, in the framework of (complete and incomplete) ranking data, the impact of the differently structured weighted distances for building decision trees. The traditional metrics between rankings don’t take into account the importance of swapping elements similar among them (element weights) or elements belonging to the top (or to …

weighted distances ranking Kemeny consensus treesSettore SECS-S/01 - Statistica
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