Windows-10-10.0.10586
Python 3.4.4 |Continuum Analytics, Inc.| (default, Jan 29 2016, 15:20:20) [MSC v.1600 64 bit (AMD64)]
NumPy 1.10.4
SciPy 0.17.0
Scikit-Learn 0.17.1

import numpy as np
from sklearn.gaussian_process import GaussianProcess

X = np.random.rand(100, 3)
y = np.random.rand(100)

gp = GaussianProcess().fit(X, y)

gp.predict(X, batch_size=5)

'float' object cannot be interpreted as an integer

C:\...\lib\site-packages\sklearn\gaussian_process\gaussian_process.py in predict(self, X, eval_MSE, batch_size)
    520 
    521                 y = np.zeros(n_eval)
--> 522                 for k in range(max(1, n_eval / batch_size)):
    523                     batch_from = k * batch_size
    524                     batch_to = min([(k + 1) * batch_size + 1, n_eval + 1])

TypeError: 'float' object cannot be interpreted as an integer