binary classification

collocation in English

meaningsofbinaryandclassification

These words are often used together. Click on the links below to explore the meanings. Or,see other collocations withclassification.
binary
adjective
uk
/ˈbaɪ.nər.i/us
/ˈbaɪ.ner.i/
mathematics,computingspecialized
using a system of numbers that uses only 0 ...
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classification
noun
uk
/ˌklæs.ɪ.fɪˈkeɪ.ʃən/us
/ˌklæs.ə.fəˈkeɪ.ʃən/
the act or process of dividing things into groups according to ...
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(Definition ofbinaryandclassificationfrom theCambridge English Dictionary© Cambridge University Press)

Examplesofbinary classification

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.
The approach achieved an accuracy of approximately 80% on thebinaryclassificationtask.
From theCambridge English Corpus
The two algorithms are tested on abinaryclassificationproblem.
From theCambridge English Corpus
This permitted abinaryclassificationof observed compliance.
From theCambridge English Corpus
However, thebinaryclassificationon each measure generated risk groups with only limited overlap.
From theCambridge English Corpus
Thebinaryclassificationof "alcoholic" or "not alcoholic" does not carry enough information to adequately characterize differences in the natural history of the disorder.
From theCambridge English Corpus
Mayhew denies that abinaryclassificationof elections, as realigning or insignificant, can be made.
From theCambridge English Corpus
Since many classification methods have been developed specifically forbinaryclassification, multiclass classification often requires the combined use of multiple binary classifiers.
From
Wikipedia
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Here logistic regression is being used as abinaryclassificationmodel.
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We can determine the keyphrases by looking atbinaryclassificationdecisions or probabilities returned from our learned model.
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Inbinaryclassification, a better understood task, only two classes are involved, whereas multiclass classification involves assigning an object to one of several classes.
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Inbinaryclassification, recall is often called sensitivity.
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Some classifiers make abinaryclassificationfor a test example, while others assign a probability of being a keyphrase.
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Let us consider a two-class prediction problem (binaryclassification), in which the outcomes are labeled either as positive ("p") or negative ("n").
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Binaryclassificationmethods include probit regression and logistic regression.
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Inbinaryclassification, precision is analogous to positive predictive value.
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Problem transformation methods transform the multi-label problem into a set ofbinaryclassification problems, which can then be handled using single-class classifiers.
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For example, forbinaryclassificationproblems, each case in the validation set is either predicted correctly or incorrectly.
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Abinaryclassificationis such that the label "y" can take only a two values.
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An example of learning which is not inductive would be in the case ofbinaryclassification, where the inputs tend to cluster in two groups.
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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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See other collocations withclassification