http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-113962325-A

Outgoing Links

Predicate Object
assignee http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_3fae430a74d0c40608e75ad1a938e0ac
classificationCPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-214
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-241
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-045
classificationIPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-04
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62
filingDate 2021-11-09-04:00^^<http://www.w3.org/2001/XMLSchema#date>
inventor http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_7ebe1c5b308488835e30ecea4c49de3a
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_36c35c9efcbd0bea37299b306b48a01f
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_c2493cb47dfea897cdfafde3e14c1b2f
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_182b7d338ffe19306d8fd7e3c713585a
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_e8464c858d2add9ff201205b9b4ce6fb
publicationDate 2022-01-21-04:00^^<http://www.w3.org/2001/XMLSchema#date>
publicationNumber CN-113962325-A
titleOfInvention A Remotely Supervised Dataset Denoising Method
abstract The invention discloses a method for denoising a remote supervised data set. First, the DS data set is divided into positive sample set TD and negative sample set FD according to whether the data has labels, and then TD is extracted by a pattern-based data extraction algorithm The medium and high-quality positive example set CTD, using CTD and FD, trains a binary classification model Filter-Net, which can accurately identify high-quality negative example set CFD from FD. Finally, the high-quality negative sample set CFD, together with the positive sample set TD, is used as the training data set of the RL model to obtain a higher-quality correctly labeled sample set. Starting from making full use of the wrongly labeled data in the DS data set, the present invention proposes a method for extracting high-quality positive sample and negative sample data from the DS data set, and uses the high-quality positive sample and negative sample data for the desiccation model training, thereby improving the accuracy of the de-drying model and achieving the purpose of effective de-drying.
priorityDate 2021-11-09-04:00^^<http://www.w3.org/2001/XMLSchema#date>
type http://data.epo.org/linked-data/def/patent/Publication

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isDiscussedBy http://rdf.ncbi.nlm.nih.gov/pubchem/substance/SID416225796
http://rdf.ncbi.nlm.nih.gov/pubchem/compound/CID3036909

Total number of triples: 20.