I am trying to use train_test_split from package scikit Learn, but I am having trouble with parameter stratify. Hereafter is the code:
from sklearn import cross_validation, datasets
X = iris.data[:,:2]
y = iris.target
cross_validation.train_test_split(X,y,stratify=y)
However, I keep getting the following problem:
raise TypeError("Invalid parameters passed: %s" % str(options))
TypeError: Invalid parameters passed: {'stratify': array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2])}
Does someone have an idea what is going on? Below is the function documentation.
[...]
stratify : array-like or None (default is None)
If not None, data is split in a stratified fashion, using this as the labels array.
New in version 0.17: stratify splitting
[...]
Scikit-Learn is just telling you it doesn't recognise the argument "stratify", not that you're using it incorrectly. This is because the parameter was added in version 0.17 as indicated in the documentation you quoted.
So you just need to update Scikit-Learn.