Is your feature request related to a problem? Please describe.
In the machine learning pipelines, you can use different trainer methods when adding a model candidate, such as RandomForest or MLP.
For MLP, we could expose more parameters to configure.
Is your feature request related to a problem? Please describe. In the machine learning pipelines, you can use different trainer methods when adding a model candidate, such as RandomForest or MLP. For MLP, we could expose more parameters to configure.
Current exposed parameters are listed at https://neo4j.com/docs/graph-data-science/current/machine-learning/training-methods/mlp/.
Describe the solution you would like
We could also expose other optional parameters such as:
These are just examples, you could also come up with others.
Additional context
Good starting points are
MLPClassifierTrainConfigandMLPClassifierIf you want to work on this issue please drop a comment :)