The phrase "are trained on data" is correct and usable in written English.
It can be used when discussing the process by which models or systems learn from datasets.
Example: "Machine learning algorithms are trained on data to improve their accuracy and performance."
Alternatives: "are educated using data" or "are developed based on data".
Many machine learning classifiers are trained on data labeled by humans.
If these models are trained on data going back several decades, but there have been structural changes in the U.S. economy since then, that could explain why these forecasts are consistently missing to the high side.
Systems are trained on data without background noise and performance [6] tend to degrade in noisy environments.
There is growing concern that many of the algorithms that make decisions about our lives - from what we see on the internet to how likely we are to become victims or instigators of crime - are trained on data sets that do not include a diverse range of people.
They were also asked if the providers are trained on data collection, analysis, and reporting.
In particular, when the SVMs are trained on data from Donor B, the ability to predict dysbiosis in Donor A is worse than random.
This is traditionally achieved through a process called supervised learning, where the machine is trained on data that is a one-to-one match.
A flying foreman: The drones use AI that has been trained on data like labeled aerial YouTube footage depicting different kinds of industrial equipment.
A predictive computational model that was trained on data obtained in the task context outperformed a model that was trained under the abstract context.
Since it is trained on data from L1-English speakers, the system can be used on English utterances spoken by speakers of any L1 without retraining.
Since during AE monitoring not all events can be guaranteed to be detected by all sensors, a GP was trained on data for all possible combinations (subsets) of sensors.
