The phrase "are trained using a" is correct and usable in written English.
It can be used when describing the method or process by which someone or something is educated or developed, often in a technical or professional context.
Example: "The models are trained using a variety of algorithms to improve their accuracy and performance."
Alternatives: "are educated with a" or "are developed through a".
Classifiers built in this way are unlikely to be useful as diagnostic tools unless they are trained using a very large number of samples that better approximates the target population for the tool.
However, if the models are trained using a dataset that contains a limited range of values, they may perform poorly when encountering events containing previously unobserved values.
Moreover, to reduce the computational cost of the ensemble and to improve its performance, these classifiers are trained using a specific attribute subset.
The NNs are trained using a database of archived data describing the relationship between the output parameter and an input space.
To design the generative stage, multiple discrete left-to-right Hidden Markov Models (HMMs) are trained using a different number of states and codebook sizes, allowing the system to learn signatures at different levels of perception.
The SVMs are trained using a sequential minimum optimization (SMO) method as described in [34].
An ANN is trained using a back propagation with Levenberg Marquardt algorithm.
A Support Vector Regression (SVR) model was trained using a diffusion kernel obtained from this graph's Laplacian matrix.
In Experiment 1, chicks were trained using a silver-coloured bead coated with 100% MeA, 0.5% DB or distilled water.
The artificial neural network was trained using a hybrid learning method based on Simulated Annealing and Levenberg Marquardt method.
The neural network model was trained using a carefully selected training signal that contained all the relevant process and controller dynamics.
