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In computer vision, the bag-of-words model (BoW model) sometimes called bag-of-visual-words model [1] [2] can be applied to image classification or retrieval, by treating image features as words. In document classification , a bag of words is a sparse vector of occurrence counts of words; that is, a sparse histogram over the vocabulary.
The bag-of-words model (BoW) is a model of text which uses an unordered collection (a "bag") of words. It is used in natural language processing and information retrieval (IR). It disregards word order (and thus most of syntax or grammar) but captures multiplicity .
Only patients in the bootstrap sample would be used to train the model for that bag. This example shows how bagging could be used in the context of diagnosing disease. A set of patients are the original dataset, but each model is trained only by the patients in its bag. The patients in each out-of-bag set can be used to test their respective ...
For example, a model that produces 50 trees using the bootstrap/out-of-bag datasets will have a better accuracy than if it produced 10 trees. Since the algorithm generates multiple trees and therefore multiple datasets the chance that an object is left out of the bootstrap dataset is low.
By mapping each bag to a feature vector of metadata, metadata-based algorithms allow the flexibility of using an arbitrary single-instance algorithm to perform the actual classification task. Future bags are simply mapped (embedded) into the feature space of metadata and labeled by the chosen classifier.
Viewdata is a Videotex implementation. It is a type of information retrieval service in which a subscriber can access a remote database via a common carrier channel , request data and receive requested data on a video display over a separate channel.
For example, word2vec has been used to map a vector space of words in one language to a vector space constructed from another language. Relationships between translated words in both spaces can be used to assist with machine translation of new words.
Some collections maintain a linear ordering of items – with access to one or both ends. The data structure implementing such a collection need not be linear. For example, a priority queue is often implemented as a heap, which is a kind of tree. Notable linear collections include: list; stack; queue; priority queue; double-ended queue