Learning with Partially Labeled and Interdependent Data
Consider the supervised learning task, where the prediction function, which infers a predicted output for a given input, is learned over a finite set of labeled training examples, where each instance of this set is a pair constituted of a vector characterizing an observation in a given vector spac...
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| Ngôn ngữ: | English |
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2015
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oai:scholar.dlu.edu.vn:DLU123456789-561402023-11-11T05:32:38Z Learning with Partially Labeled and Interdependent Data Amini, Massih-Reza Usunier, Nicolas Data Partially Labeled Consider the supervised learning task, where the prediction function, which infers a predicted output for a given input, is learned over a finite set of labeled training examples, where each instance of this set is a pair constituted of a vector characterizing an observation in a given vector space, and an associated desired response for that instance (also called desired output). After the training step, the function returned by the algorithm is sought to give predictions on new examples, which have not been used in the learning process, with the lowest probability of error... 2015-06-11T02:11:47Z 2015-06-11T02:11:47Z 2015 Book 978-3-319-15725-2 https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/56140 en application/pdf Springer |
| institution |
Thư viện Trường Đại học Đà Lạt |
| collection |
Thư viện số |
| language |
English |
| topic |
Data Partially Labeled |
| spellingShingle |
Data Partially Labeled Amini, Massih-Reza Usunier, Nicolas Learning with Partially Labeled and Interdependent Data |
| description |
Consider the supervised learning task, where the prediction function, which infers
a predicted output for a given input, is learned over a finite set of labeled training
examples, where each instance of this set is a pair constituted of a vector characterizing an observation in a given vector space, and an associated desired response
for that instance (also called desired output). After the training step, the function
returned by the algorithm is sought to give predictions on new examples, which have
not been used in the learning process, with the lowest probability of error... |
| format |
Book |
| author |
Amini, Massih-Reza Usunier, Nicolas |
| author_facet |
Amini, Massih-Reza Usunier, Nicolas |
| author_sort |
Amini, Massih-Reza |
| title |
Learning with Partially Labeled and Interdependent Data |
| title_short |
Learning with Partially Labeled and Interdependent Data |
| title_full |
Learning with Partially Labeled and Interdependent Data |
| title_fullStr |
Learning with Partially Labeled and Interdependent Data |
| title_full_unstemmed |
Learning with Partially Labeled and Interdependent Data |
| title_sort |
learning with partially labeled and interdependent data |
| publisher |
Springer |
| publishDate |
2015 |
| url |
https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/56140 |
| _version_ |
1819775857213833216 |