Hardness of the Cost-sensitive Classification Problem
Cost-sensitive online classification
... both cost-sensitive classification and online learning have been studied extensively in data mining and machine learning communities, respectively, there were very few comprehensive studies on ...
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Adaptive cost-sensitive online classification
... of cost-sensitive online classification algorithms with adaptive regularization in this ...solving cost-sensitive online classification problems in various real-world ...
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Active Learning for Cost-Sensitive Classification
... binary classification, where one estimates the class-conditional regression function (Castro and Nowak, 2008; Minsker, 2012; Hanneke and Yang, 2012; Car- pentier et ...
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Cost-sensitive Multiclass Classification Risk Bounds
... Previous work has uncovered sufficient and necessary conditions for the consistency of the resulting procedures. In this paper, we strengthen these results by showing how the 0 − 1 excess loss of a predictor can be upper ...
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Cost sensitive online multiple kernel classification
... of cost, have caused a great reduction of the cost ...the cost suffered by kernel methods is a mere 7% of the cost suffered by the best linear ...multiple cost-sensitive kernel ...
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Distributed AdaBoost Extensions for Cost sensitive Classification Problems
... Fig. 3: MapReduce of DDT This whole mechanism leads to the following problems. First, the Model Experience Problem. If the user supplies hundred partitions as an input, there will be an ensemble of hundred trees ...
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An Empirical Evaluation of AdaBoost Extensions for Cost Sensitive Classification
... instances. Cost-sensitive classifier is relatively new field of research in the data mining and machine learning ...for classification tasks under the cost-based model, unlike the error-based ...
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Online Cost-Sensitive Learning for Efficient Interactive Classification
... online cost-sensitive learning approach (more-like-this) that fo- cuses on reducing the time it takes for the experts to review and label examples in inter- active machine learning ...the problem of ...
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CogBoost: Boosting for Fast Cost-Sensitive Graph Classification
... Fast Cost-sensitive Graph Classification Shirui Pan, Jia Wu, and Xingquan Zhu, Senior Member, IEEE Abstract—Graph classification has drawn great interests in recent years due to the increasing ...
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Cost-sensitive Naïve Bayes Classification of Uncertain Data
... of cost sensitive algorithm on uncertain ...novel cost-sensitive Naïve Bayes algorithm CS-DTU for classifying and predicting uncertain ...total cost, and propose a new test strategy for ...
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ROC-based cost-sensitive classification with a reject option
... real-world classification tasks, such as med- ical diagnosis, it is crucial to take into account misclassification costs for designing an accurate classification ...a cost-sensitive classi- ...
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TRANSDUCTIVE BASED COST-SENSITIVE MULTI-LABEL CLASSIFICATION
... the problem of multi-label classification gain huge ...Multi-label classification problem includes example which belongs to multiple ...multi-label classification concentrated on ...
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Cost-Sensitive Label Embedding for Multi-Label Classification
... different cost functions of ...specific cost function, but they can suffer from bad performance with respect to other cost ...novel cost-sensitive LE algorithm that takes the ...
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Low Size-Complexity Inductive Logic Programming: The East-West Challenge Considered as a Problem in Cost-Sensitive Classification
... sentation. Although the second competition was intended for sub-symbolic and semi- symbolic inductive analysis, symbolic learners were not forbidden. The second competi- tion involved classifying 100 new trains, using a ...
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Cost Sensitive BERT for Generalisable Sentence Classification on Imbalanced Data
... training data, that are common in literature (Ling and Sheng, 2011). Rather than directly using the class proportions of the training set, we show that tuning weights based on performance on the de- velopment set is more ...
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From Cost-Sensitive Classification to Tight F-measure Bounds
... a classification performance measure, especially suited when dealing with imbalanced datasets, which provides a com- promise between the precision and the recall of a ...using cost-sensitive learning ...
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Cost-sensitive decision tree ensembles for effective imbalanced classification
... or cost-sensitive ...of cost-sensitive decision trees for imbalanced ...given cost matrix, but are trained on random feature subspaces to ensure sufficient diversity of the ensemble ...
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Reduction from Cost-sensitive Multiclass Classification to One-versus-one Binary Classification
... Keywords: cost-sensitive classification, one-versus-one, meta-learning ...spam classification system only takes the user an extra second to delete the email, while a false-positive prediction ...
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Reduction from cost-sensitive ordinal ranking to weighted binary classification
... binary classification algorithm, and con- structing a ranker from the binary ...mislabeling cost of the ranker, both error-wise and ...binary classification approaches, but also the derivation of new ...
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One-sided Support Vector Regression for Multiclass Cost-sensitive Classification
... reduces cost-sensitive classification to one-sided re- ...the cost infor- mation in the regression labels and encodes the minimum-cost prediction with the one- sided ...a cost- ...
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