منابع مشابه
Class Imbalance and Active Learning
The rich history of predictive modeling has culminated in a diverse set of techniques capable of making accurate predictions on many real-world problems. Many of these techniques demand training, whereby a set of instances with ground-truth labels (values of a dependent variable) are observed by a model-building process that attempts to capture, at least in part, the relationship between the fe...
متن کاملthe survey of the virtual higher education in iran and the ways of its development and improvement
این پژوهش با هدف "بررسی وضعیت موجود آموزش عالی مجازی در ایران و راههای توسعه و ارتقای آن " و با روش توصیفی-تحلیلی و پیمایشی صورت پذیرفته است. بررسی اسنادو مدارک موجود در زمینه آموزش مجازی نشان داد تعداد دانشجویان و مقاطع تحصیلی و رشته محل های دوره های الکترونیکی چندان مطلوب نبوده و از نظر کیفی نیز وضعیت شاخص خدمات آموزشی اساتید و وضعیت شبکه اینترنت در محیط آموزش مجازی نامطلوب است.
Class Augmented Active Learning
Traditional active learning encounters a cold start issue when very few labelled examples are present for learning a decent initial classifier. Its poor quality subsequently affects selection of the next query and stability of the iterative learning process, resulting in more annotation effort from a domain expert. To address this issue, this paper presents a novel class augmentation technique,...
متن کاملActive Learning Literature Survey
The key idea behind active learning is that a machine learning algorithm can achieve greater accuracy with fewer labeled training instances if it is allowed to choose the data from which is learns. An active learner may ask queries in the form of unlabeled instances to be labeled by an oracle (e.g., a human annotator). Active learning is well-motivated in many modern machine learning problems, ...
متن کاملActive Learning Literature Survey
The most time consuming and expensive task in machine learning is the gathering of labeled data to train the model or to estimate its parameters. In the real-world scenario, the availability of labeled data is scarce and we have limited resources to label the abundantly available unlabeled data. Hence it makes sense to pick only the most informative instances from the unlabeled data and request...
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ژورنال
عنوان ژورنال: Teaching History: A Journal of Methods
سال: 1987
ISSN: 0730-1383
DOI: 10.33043/th.12.2.3-9