| 摘要 |
Machine learning may be personalized to individual users of personal computing devices, and can be used to increase machine learning prediction accuracy and speed, and/or reduce memory footprint. Personalizing machine learning can include selecting a subset of a machine learning model to load into memory. Such selecting is based, at least in part, on information collected locally by the personal computing device. Personalizing machine learning can additionally or alternatively include adjusting a classification threshold of the machine learning model based, at least in part, on the information collected locally by the personal computing device. Moreover, personalizing machine learning can additionally or alternatively include normalizing a feature output of the machine learning model accessible by an application based, at least in part, on the information collected locally by the personal computing device. |
