نتایج جستجو برای: multi label classification
تعداد نتایج: 981326 فیلتر نتایج به سال:
Label powerset (LP) method is one category of multi-label learning algorithm. This paper presents a basis expansions model for multi-label classification, where a basis function is a LP classifier trained on a random k-labelset. The expansion coefficients are learned to minimize the global error between the prediction and the ground truth. We derive an analytic solution to learn the coefficient...
Conventional multi-label classification algorithms treat the target labels of the classification task as mere symbols that are void of an inherent semantics. However, in many cases textual descriptions of these labels are available or can be easily constructed from public document sources such as Wikipedia. In this paper, we investigate an approach for embedding documents and labels into a join...
This paper introduces “Czech Text Document Corpus v 2.0”, a collection of text documents for automatic document classification in Czech language. It is composed of 11,955 text documents provided by the Czech News Agency and is freely available for research purposes at http://home.zcu.cz/ ̃pkral/sw/ . This corpus was created in order to facilitate a straightforward comparison of the document clas...
Multi-label classification is an important learning problemwith many applications. In this work, we propose a principled similarity-based approach for multi-label learning called SML. We also introduce a similarity-based approach for predicting the label set size. The experimental results demonstrate the effectiveness of SML for multi-label classification where it is shown to compare favorably ...
This paper presents an overview of the ImageCLEF 2016 evaluation campaign, an event that was organized as part of the CLEF (Conference and Labs of the Evaluation Forum) labs 2016. ImageCLEF is an ongoing initiative that promotes the evaluation of technologies for annotation, indexing and retrieval for providing information access to collections of images in various usage scenarios and domains. ...
Multi-label feature selection is regarded as one of the most promising techniques that can be used to maximize the efficacy and efficiency of multi-label classification. However, because multi-label feature selection algorithms must consider multiple labels concurrently, the task is more difficult than singlelabel feature selection tasks. In this paper, we propose the Mutual Information-based m...
In this paper we introduce multi-label ferns, and apply this technique for automatic classification of musical instruments in audio recordings. We compare the performance of our proposed method to a set of binary random ferns, using jazz recordings as input data. Our main result is obtaining much faster classification and higher F-score. We also achieve substantial reduction of the model size.
The WISE 2014 challenge was concerned with the task of multi-label classification of articles coming from Greek print media. Raw data comes from the scanning of print media, article segmentation, and optical character segmentation, and therefore is quite noisy. Each article is examined by a human annotator and categorized to one or more of the topics being monitored. Topics range from specific ...
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