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Setting a random_state has no effect since shuffle is False #2

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@Quaterion

I try to run the sample code from the readme but get an error message:

# load libraries
from nestedhyperboost import xgboost
from sklearn import datasets
import pandas

# load data
data_sklearn = datasets.load_iris()
data = pandas.DataFrame(data_sklearn.data, columns = data_sklearn.feature_names)
data['target'] = pandas.Series(data_sklearn.target)

# conduct nestedhyperboost
results = xgboost.xgb_ncv_classifier(
    data = data,
    y = 'target',
    k_inner = 5,
    k_outer = 5,
    n_evals = 10
)

  0%|          | 0/10 [00:00<?, ?trial/s, best loss=?]job exception: Setting a random_state has no effect since shuffle is False. You should leave random_state to its default (None), or set shuffle=True.

[...]


  File "C:\\Miniconda3\lib\site-packages\sklearn\model_selection\_split.py", line 290, in __init__
    raise ValueError(

 ValueError: Setting a random_state has no effect since shuffle is False. You should leave random_state to its default (None), or   set shuffle=True.

Versions:
version('nestedhyperboost')
'0.0.3'
version('pandas')
'1.2.0'
version('sklearn')
'0.0'

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