Lasso type classifiers with a reject option
نویسندگان
چکیده
منابع مشابه
Lasso type classifiers with a reject option
This paper discusses structural risk minimization in the setting of classification with a reject option. Binary classification is about classifying observations that take values in an arbitrary feature space X into one of two classes, labelled −1 or +1. A discriminant function f : X → R yields a classifier sgn(f(x)) ∈ {−1,+1} that represents our guess of the label Y of a future observation X an...
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Consider the class of problems in which a target class is well defined, and an outlier class is ill-defined. In these cases new outlier classes can appear, or the classconditional distribution of the outlier class itself may be poorly sampled. A strategy to deal with this problem involves a two-stage classifier, in which one stage is designed to perform discrimination between known classes, and...
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can be obtained using the so-called “reject” option. Namely, the patterns that are the most likely to be misclassified are rejected (i.e., they are not classified); they are then handled by more sophisticated procedures (e.g., a manual classification is performed). However, handling high reject rates is usually too time-consuming for application purposes. Therefore, a trade-off between error an...
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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<...
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ژورنال
عنوان ژورنال: Electronic Journal of Statistics
سال: 2007
ISSN: 1935-7524
DOI: 10.1214/07-ejs058