dimensionality reduction
collocation in Englishmeaningsofdimensionalityandreduction
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dimensionality
noun[U]
uk/ˌdaɪ.men.ʃənˈæl.ə.ti/us/dɪ.men.ʃənˈæl.ə.t̬i/
approving
the quality of having many different features or qualities, especially in a way that makes something seem real, rather than being ...
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reduction
noun
uk/rɪˈdʌk.ʃən/us/rɪˈdʌk.ʃən/
the act of making something, or of something becoming, smaller in size, amount, degree, ...
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(Definition ofdimensionalityandreductionfrom theCambridge English Dictionary© Cambridge University Press)
Examplesofdimensionality reduction
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.
Chapter 6 starts with a compelling case for both feature selection and feature extraction, both of which can help withdimensionalityreduction.
From theCambridge English Corpus
At present, the dominant approach todimensionalityreductionin epidemiological inquiry is through the use of multivariable models.
From theCambridge English Corpus
Finally, we discuss the implications of functional features for object categorization, conceptual development, chunking, constructive induction, and formal models ofdimensionalityreduction.
From theCambridge English Corpus
Preprocessing was again used indimensionalityreductionto create feature vectors, and categorization proceeded as a sequential process based on manual selection of diagrams.
From theCambridge English Corpus
The success of time series prediction tasks depends on various issues, including problemdimensionalityreduction, context representation, as well as knowledge representation and acquisition.
From theCambridge English Corpus
Afterdimensionalityreductionhas been performed, a system of inequalities remains to be solved.
From theCambridge English Corpus
The following subsections describe some widely accepted methods of performingdimensionalityreduction.
From theCambridge English Corpus
What is required is a representation that makes a compromise betweendimensionalityreductionand information loss.
From theCambridge English Corpus
Although previous researchers have addressed this problem with an unsuperviseddimensionalityreduction algorithm,21 this method did not exploit physical class knowledge that could be inherited from supervised classifiers.
From theCambridge English Corpus
A different approach to nonlineardimensionalityreductionis through the use of autoencoders, a special kind of feed-forward neural networks with a bottle-neck hidden layer.
From
Wikipedia
Many of these non-lineardimensionalityreductionmethods are related to the linear methods listed below.
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Wikipedia
Dimensionalityreductionmay also be appropriate when the variables in a dataset are noisy.
From
Wikipedia
The linear filtering stage performsdimensionalityreduction, reducing the high-dimensional spatio-temporal stimulus space to a low-dimensional feature space, within which the neuron computes its response.
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Wikipedia
A remedy to this problem is to reduce the number of features in an informative sense (seedimensionalityreduction).
From
Wikipedia
They have been found to be particularly useful for rule induction and feature selection (semantics-preservingdimensionalityreduction).
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Wikipedia
In order to reduce the dimensionality of the feature space, a number ofdimensionalityreductiontechniques can be employed.
From
Wikipedia
The resulting combination may be used as a linear classifier, or, more commonly, fordimensionalityreductionbefore later classification.
From
Wikipedia
Therefore,dimensionalityreductionis frequently employed to map high-dimensional data to a low-dimensional space while retaining as much information as possible.
From
Wikipedia
The created data space is then usually reduced by a following feature extraction (see alsodimensionalityreduction).
From
Wikipedia
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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