The title basically says it all. I want to try different hyperparameters for my Neural Network (or algorithms in general). For some, like random forest, I can specify a list - e.g., max_depth. What I need is a queue of Neural Networks with different hyperparameters, so that I can start them in the evening and come back to the results in the morning.
How to do this?
It is not possible at the moment on the visual interface.
Instead, for hyperparameter optimization on neural networks, we invite you to code your own custom Python model (in the Analysis > Design > Algorithms section). For instance, for a neural network from scikit-learn (MLP), you can use this:
from sklearn.neural_network import MLPClassifier
from sklearn.model_selection import GridSearchCV
'activation': ["logistic", "relu"]
mlp = MLPClassifier()
clf = GridSearchCV(
Note that we are looking to integrate neural networks more deeply 😉 into our product. We will keep you posted!