# Kernel dies or proses stuck when making LR prediction on dataframe using apply

I'm trying to making predictions with a simple model.

model=LogisticRegression()
model.fit(X_train,y_train)


After fitting, i try to make predictions. A sample X_test value and the code is below.

X_train[41626]

array([-0.53668182,  0.57287544, -1.48834257, -0.6080626 , -0.86691148,
0.24336571,  0.        ,  0.53303864, -0.05081621,  0.17409271,
-0.21513622, -1.15424615,  0.74731522,  1.47161341])


The model fits in like 5 seconds. After below code is executed, when it gets to %5 or %6 it stops for a long time (the last stop point was 39938/326232). Sometimes kernel dies, sometimes it just stops. It stops at random row btw.

test['Predicted'] = test.progress_apply(lambda x: model.predict(X_train) ,axis=1)


I have updated all python libraries and try this code on both a windows and mac m1 machine. The result is the same.

What is the problem? I cant figure it out.

• Full traceback, full model please Nov 11 '21 at 12:23

test['Predicted'] = test.apply(lambda x: model.predict(x.values.reshape(-1, len(test.columns))), axis=1)