I'm running this Code:
from scipy.stats.stats import pearsonr
y_test = y_test.astype(float)
y_predicted = y_predicted.astype(float)
print (pearsonr(y_test, y_predicted))
y_train_predict = model.predict(X_train)
print (pearsonr(y_train, y_train_predict))
when y_predicted is coming out of keras model like y_train_predict, and y_test and y_train are just arrays.
I get the following error:
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-29-3cdf50a9131b> in <module>()
2 y_test = y_test.astype(float)
3 y_predicted = y_predicted.astype(float)
----> 4 print (pearsonr(y_test, y_predicted))
5 y_train_predict = model.predict(X_train)
6 print (pearsonr(y_train, y_train_predict))
~/.conda/envs/kerasenv/lib/python3.6/site-packages/scipy/stats/stats.py in pearsonr(x, y)
3411 r_{pb} = \frac{\overline{Y_{1}} -
3412 \overline{Y_{0}}}{s_{y}}\sqrt{\frac{N_{1} N_{2}}{N (N - 1))}}
-> 3413
3414 Where :math:`Y_{0}` and :math:`Y_{1}` are means of the metric
3415 observations coded 0 and 1 respectively; :math:`N_{0}` and :math:`N_{1}`
~/.conda/envs/kerasenv/lib/python3.6/site-packages/numpy/core/_methods.py in _mean(a, axis, dtype, out, keepdims)
149 return ret
150
--> 151 def _ptp(a, axis=None, out=None, keepdims=False):
152 return um.subtract(
153 umr_maximum(a, axis, None, out, keepdims),
TypeError: No loop matching the specified signature and casting was found for ufunc add
The interesting thing that this problem happens only when I run the code on INTEL@Devcloud server. When I run this on python of my laptop is running fine.