Classification with reject option
نویسندگان
چکیده
منابع مشابه
Multi-label classification with a reject option
We consider multi-label classification problems in application scenarios where classifier accu-racy is not satisfactory, but manual annotation is too costly. In single-label problems, a wellknown solution consists of using a reject option, i.e., allowing a classifier to withhold unreliabledecisions, leaving them (and only them) to human operators. We argue that this solution can be<...
متن کاملConsistent Algorithms for Multiclass Classification with a Reject Option
We consider the problem of n-class classification (n ≥ 2), where the classifier can choose to abstain from making predictions at a given cost, say, a factor α of the cost of misclassification. Designing consistent algorithms for such n-class classification problems with a ‘reject option’ is the main goal of this paper, thereby extending and generalizing previously known results for n = 2. We sh...
متن کاملClassification Methods with Reject Option Based on Convex Risk Minimization
In this paper, we investigate the problem of binary classification with a reject option in which one can withhold the decision of classifying an observation at a cost lower than that of misclassification. Since the natural loss function is non-convex so that empirical risk minimization easily becomes infeasible, the paper proposes minimizing convex risks based on surrogate convex loss functions...
متن کاملClassification with reject option in gene expression data
MOTIVATION The classification methods typically used in bioinformatics classify all examples, even if the classification is ambiguous, for instance, when the example is close to the separating hyperplane in linear classification. For medical applications, it may be better to classify an example only when there is a sufficiently high degree of accuracy, rather than classify all examples with dec...
متن کاملClassification with Reject Option Using the Self-Organizing Map
Reject option is a technique used to improve classifier’s reliability in decision support systems. It consists on withholding the automatic classification of an item, if the decision is considered not sufficiently reliable. The rejected item is then handled by a different classifier or by a human expert. The vast majority of the works on this issue have been concerned with implementing a reject...
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ژورنال
عنوان ژورنال: Canadian Journal of Statistics
سال: 2006
ISSN: 0319-5724,1708-945X
DOI: 10.1002/cjs.5550340410