| 词汇 | example_english_unsupervised |
| 释义 | Examples of unsupervisedThese examples are from corpora and from sources on the web. Any opinions in the examples do not represent the opinion of the Cambridge Dictionary editors or of Cambridge University Press or its licensors. Unsupervised learning of the morphology of a natural language. Neither supervised nor unsupervised learning from corpora expresses this task. They are based on splitting methods, search algorithms, supervised and unsupervised neural networks, description logic and semantic networks. Because classification was unsupervised, it was not possible to apply these evaluation methods directly as would be the case for supervised learning. The fourth stage continues as an interactive process that moves from unsupervised categorization to one that is guided by the observer. The network uses an unsupervised learning algorithm to generate a mapping between the high-dimensional design space of component parameters and the neurons in the network. Their leisure time was unsupervised, their cells were unlocked and had no iron bars. In both cases, the network is self-organizing and unsupervised. The most natural assumption is that, at some level, local unsupervised featural learning is carried out. The wandering construct was a measure of the target boy's unsupervised time, primarily outside the home. In the framework developed here, supervised learning is a simple extension of the unsupervised classification learning described previously. Basic but usable estimators for unsupervised classification, supervised classification, time-series and sequence analysis have been presented. Unsupervised efficient learning and representation of language structure. Other unsupervised work has gone beyond the task of verb clustering to that of verb argument structure induction. To create useful classes, unsupervised verb class discovery will require some sort of manual identification of linguistically relevant properties to guide the process. In this paper, we present an unsupervised algorithm for discovering inference rules from text. Still, such methods employ a very light-weight notion of topicality, with themes derived, indirectly, via unsupervised clustering. Unsupervised learning involves acquisition of lexical knowledge and rules from a raw corpus. They admitted later that they preferred working unsupervised as they could experiment more. In the absence of a priori knowledge, unsupervised or clustering methods seem to be ideally suited to the categorization of the user information interests. An unsupervised condition type, however, explicitly models conditions that are outside the scope of a schema's responsibility. Xu et al.'s approach (2002) is designed to acquire domain-relevant terms and their relations using unsupervised hybrid text-mining techniques. When unsupervised, children may wash their hands poorly. We presented a technique for fully unsupervised statistical acquisition of rules which guess possible parts of speech for words unknown to the lexicon. The full-resolution image was classified using a hybrid supervised-unsupervised approach, initially into 40 image classes. The issue of control was not simply fear of unsupervised activity. Neural networks can be classified into two categories: supervised and unsupervised learning methods. In this way, initial unsupervised clustering can become more accurate according to a designer's intentions as new clusters are formed. The learning time includes the time spent on unsupervised and supervised learning. All nations should move to restrict unsupervised access of people to antibiotics. In addition, low-income students were comparatively more often unsupervised by adults after school. Unsupervised learning has inputs xj but no given target responses yj associated to them. A hierarchical unsupervised growing neural network for clustering gene expression patterns. The remaining, unmasked areas were classified by first performing an unsupervised classification initialised to 30 clusters. The unsupervised reestimation algorithm works in two steps. Our experiments also showed that a similar previouslyproposed mostly-unsupervised algorithm could not yield comparable results. The following subsections concentrate on supervised and unsupervised methods to build models of user interests. Unsupervised methods allow agents to discover user interest categories in several domains based on clustering of experiences. In contrast, unsupervised learning methods do not require preclassification of the training examples; these algorithms form clusters of examples which share common characteristics. The control is constructed in two stages, an optimal controller and an unsupervised neural network controller using model-based predictive control. Therefore, the initial results from the unsupervised clustering are displayed using the topographic map so that weights can be derived from user input. Non-linear networks may be trained using supervised learning, learning by example with outputs, or unsupervised learning, self-organizing without outputs. An unsupervised nonabused young child is more likely to witness interpersonal traumas such as domestic and community violence or to experience traumatic accidents. The main reason for change to these unsupervised radiographs (8% of the sample) was caused by incomplete instructions from the medical staff. Unsupervised learning or clustering is a division of data into groups of similar objects. An alternative way to exploring possible sets of dialogue act types is by unsupervised learning of dialogue act classes, based on superficial utterance features. One way to overcome this problem is to use unsupervised learning algorithms which do not learn from examples but from observations. Unsupervised learning has mainly been used for concept formation based on similarity between observations. An important consequence of this move is that sense assignment is based on a considerable amount of unsupervised data, through a sample of sense seeds. We will refer to this partition as the 'unsupervised task'. Combining unsupervised lexical knowledge methods for word sense disambiguation. When the dependency system is combined with their unsupervised constituency grammar, the integrated model outperforms each of these systems. Unsupervised learning is distinguished from supervised learning by the fact that there is no a priori knowledge of the target outputs. To study the realistic problem of unsupervised classification (also known as clustering), mixture modelling and an associated search algorithm are defined. Spread via faecal-oral contact appears to require compromised levels of hygiene so that it is more common among very young children and unsupervised older children. Sites were selected on the basis of preliminary (pre-fieldwork) unsupervised classification of the image, and observations during fieldwork. A comparison of clustering strategies for unsupervised classification. Indeed, the non-selection of an information item does not necessarily mean disinterest, which makes it difficult to capture examples even to be used in unsupervised learning. Mixture models are used in unsupervised classification, also known as clustering, where a component is sometimes called a class but that is too dangerous a word in this context. When this is not the case the telerobotic device would be required to respond to a series of user commands and operate essentially unsupervised while a task is in progress. Given that approaches based on completely unsupervised learning are still vastly inferior in terms of accuracy, there is consequently a need for supervised approaches that are resilient against data sparseness. The method is unsupervised (no manual tagging of the learning corpus is needed), but requires some initial knowledge in order to learn contexts of each semantic category. A prototype for unsupervised analysis of tissue microarrays for cancer research and diagnostics. Comparing supervised and unsupervised category learning. A minimum description length framework for unsupervised learning. Style learning in the street is what psychologists call unsupervised learning; that is, it does not involve doing a task and getting feedback on how well one has done. Such sequential clustering, which is first clustering using an unsupervised network and then clustering the output map, facilitates visualizing clusters that are otherwise implicit in the output map. Machine learning experiments on grammar induction, particularly those involving unsupervised learning, can contribute important insights into the necessary conditions for language acquisition, at the least by vitiating poverty-of-stimulus arguments. Section 2 describes our mostly-unsupervised, knowledge-lean algorithm. About a third of the book is devoted to pattern recognition, covering supervised and unsupervised classification, applications of neural networks, clustering and separability, and expert systems. Probabilistic principles in unsupervised learning of visual structure: human data and a model. An unsupervised approach to recognising discourse relations. Unsupervised learning of natural languages. Unsupervised language acquisition : theory and practice. Active and unsupervised learning for automatic u speech recognition. We view this research as a successful application of the (mostly) unsupervised learning paradigm: highquality information can be extracted from large amounts of raw data, sometimes by relatively simple means. The technique of recording unsupervised conversations of this kind provides samples of adolescent speech that reveal patterns that might be hard to obtain from interviews conducted by adults. Unsupervised learning - observation of the properties of objects without any consequential input - may also be extremely useful in forming a hypothesis space for supervised (consequential) learning. Although previous researchers have addressed this problem with an unsupervised dimensionality reduction algorithm,21 this method did not exploit physical class knowledge that could be inherited from supervised classifiers. Unsupervised word-sense disambiguation rivalling supervised methods. The usefulness of any unsupervised learning algorithm to acquire conceptual design synthesis knowledge, regardless of the par ticular model of the process adopted, would seem to be limited. Underlying this conflation is the belief that the mechanisms underlying the two types of behaviour largely overlap - more particularly, unsupervised learning is a necessary component of supervised, or association, learning. Covering virtually all aspects of supervised and unsupervised analysis methods in use today, this chapter gently introduces the reader to the mathematical rational behind clustering and component analysis. A criticism might be raised that unsupervised learning does not provide a credible model of human language acquisition because children acquire their language through semi-supervised learning in rich non-linguistic contexts. An all-subtrees approach to unsupervised parsing. There are two main aspects to classification: discrimination and clustering, or supervised and unsupervised learning. Such activities went on unsupervised and therefore uncommented upon. The process of pattern compression and classification described so far is an unsupervised learning mechanism. The benefit is the elimination of training time in an unsupervised learning process. No father or older brother was willing to allow his daughter or sister to meet a boy before marriage, especially if this was unsupervised. Unsupervised young women on night-time streets could denote vice or vulnerability. The unsupervised clustering method simply classifies genes based on their expression patterns across treatments or conditions without resorting to any prior knowledge of gene function. In this paper we present a technique for fully unsupervised acquisition of rules which guess possible parts of speech for unknown words. They characterize knowledge acquisition techniques on a scale ranging from fully supervised to fully unsupervised. Unsupervised learning only processes on the input data. Equal width is one of the most frequently used unsupervised data discretization methods. An example is provided of how one author's comments to an unsupervised group of students became increasingly disciplinary. Unsupervised learning approach is employed to this model. Neural networks come in a variety of types and can be devised for supervised or unsupervised detection. I am very conscientious about meeting deadlines and completing tasks unsupervised (or supervised). These examples are from corpora and from sources on the web. Any opinions in the examples do not represent the opinion of the Cambridge Dictionary editors or of Cambridge University Press or its licensors. |
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