Closed demisak closed 5 years ago
I'm using another Autonomio package, Wrangle.
You can install it first:
pip install wrangle
And then you can split your data by:
x_train, y_train, x_val, y_val = wrangle.array_split(x, y, .3)
This would split your data 70/30.
Also note that you would generally refer to these two datasets you get after the split as "train and validation".
Closing here. Feel free to open new issue if anything.
I'm a beginner student of neural networks and I'm using Talos to optimize hyperparameters with Keras. I've got confused about how you split your dataset in train and validation in the example of Iris dataset. How did you prepare the data to use like arguments in the function like this def iris_model(x_train, y_train, x_val, y_val, params)?