| Predicate |
Object |
| assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_0fcf5693310ed0d884e1cc03f3fea3e4 |
| classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-24147
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-214 |
| classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62 |
| filingDate |
2018-05-10-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_60626744b96c24c5440bf4120d8f7717
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_6eedf1753e306818e047969c3787ecf9
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_88dc027239641d03e477d18f7a1bf1c5
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_65ca21d23956c6f4698ad3a2e81933c5
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_b25a2ce2e23e6f4c068ed1b27cdea969
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_1d586f66ea174950616925633d6560a9
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_5d26bbc1c765c636feecb86885783c93
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_eee08d50e998c295fa895749e626a2e0
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_dc8183e9db0d58082419d6970af5f422 |
| publicationDate |
2018-10-12-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber |
CN-108647727-A |
| titleOfInvention |
Unbalanced data classification undersampling method, device, equipment and medium |
| abstract |
The invention discloses an under-sampling method for unbalanced data classification, comprising: obtaining all majority samples in the unbalanced data to be processed; obtaining a minority of the k nearest neighbors of each said majority sample according to the K-nearest neighbor algorithm The number of samples; determining the category corresponding to the majority of samples according to the number of the minority samples; performing an operation corresponding to the category according to the category of each of the majority samples. Solve the problem of low accuracy of the classification learning algorithm caused by too many majority class samples and too few minority samples in the process of unbalanced big data classification, and improve the classification accuracy of unbalanced big data. |
| isCitedBy |
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-110069997-B
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-110069997-A
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-109635839-A
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-109726821-A
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-109740750-A |
| priorityDate |
2018-05-10-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type |
http://data.epo.org/linked-data/def/patent/Publication |