| 词汇 | example_english_feature-vector |
| 释义 | feature vectorcollocation in Englishmeanings of featureand vectorThese words are often used together. Click on the links below to explore the meanings. Or, see other collocations with feature or vector. feature noun uk /ˈfiː.tʃər/ us /ˈfiː.tʃɚ/ a typical quality or an important part ... See more at feature vector noun[C] uk /ˈvek.tər/ us /ˈvek.tɚ/ mathematics, physics a quantity that has both size ... See more at vector Examples of feature vectorThese 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. Using the featurevector representation, tree frames are partitioned into tree families which are subsequently used for smoothing a supertagging model. Traditional approaches can be classified into three main categories: featurevector representations, structured representations, and textual representations. Classifiers take as input a featurevector and return its estimated class. Each featurevector can be thought of as a short description of the corresponding time-frame. Note that this may overcome certain problems of smoothing using featurevector based tree families. Then, the obtained features are fused into the timedependent featurevector that characterizes the process at the designated time instants. For example, it is common practice for each case to be represented as a simple featurevector (or set of attribute-value pairs). The feature classes within the design sketch were then used to create featurevector models to classify the design corpus. The mapping from a question to a class label is a linear function defined over this featurevector. The goal of our procedure is to take as input a tree frame and then output a featurevector. However, three major types of case representation have arisen: featurevector (or propositional) cases, structured (or relational) cases, and textual (or semi-structured) cases. Each sense-tagged occurrence of a particular word is transformed into a featurevector, suitable for an automatic learning process. A featurevector is a set of attribute-value pairs. These feature vectors are then fused and a fault declaration is made based on the joint featurevector. Each case is represented as a featurevector that defines a certain category. We can define tree families for our extracted grammar in terms of the featurevector representation. An important (first) step is to map the characteristics of each genitive construction into a featurevector. The dimension of a featurevector is determined by summing up the vocabulary size for each feature. For each frame they use features and memories to calculate a featurevector. Specifically, it employs as features the continuous class likelihood outputs of the low-level classifiers as an n-dimensional featurevector for every terrain patch. 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. Want to learn more? Go to the definition of feature Go to the definition of vector See other collocations with feature See other collocations with vector |
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