Active learning relevant vector machine for reliability analysis
نویسندگان
چکیده
منابع مشابه
Active Learning with Hinted Support Vector Machine
The abundance of real-world data and limited labeling budget calls for active learning, which is an important learning paradigm for reducing human labeling efforts. Many recently developed active learning algorithms consider both uncertainty and representativeness when making querying decisions. However, exploiting representativeness with uncertainty concurrently usually requires tackling sophi...
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Music annotation is an important research topic in the multimedia area. One of the challenges in music annotation is how to reduce the human effort in labeling music files for building reliable classification models. In the past, there have been many studies on applying support vector machine active learning methods to automatic multimedia data annotation, which try to select the most informati...
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Active learning is a subfield of machine learning based on the idea that the accuracy of an algorithm can be improved with fewer training samples if it is allowed to choose the data from which it learns. We present the results for Support Vector Machine (SVM) active learning experiments for music mood tagging based on a multi-sample selection strategy that chooses samples according to their pro...
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For most algorithms we studied from our machine learning course CS545 [1], we choose training samples randomly from a large pool of labeled data, which means we know the sample classes in advance while constructing the training data set. While there is another option for selection training data: pool-based active learning, which is first introduced by Lewis and Gale in 1994 [5]. The learner can...
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ژورنال
عنوان ژورنال: Applied Mathematical Modelling
سال: 2021
ISSN: 0307-904X
DOI: 10.1016/j.apm.2020.07.034