Evaluation of Calibration Methods to Adjust for Infrequent Values in Data for Machine Learning
The performance of supervised machine learning algorithms is highly dependent on the distribution of the target variable. Infrequent values are more di_cult to predict, as there are fewer examples for the algorithm to learn patterns that contain those values. These infrequent values are a common pro...
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| Format: | Others |
| Language: | English |
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Högskolan Dalarna, Mikrodataanalys
2018
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:du-28134 |