Can any one expalin what is the error and how to aviod? The same code actually works in my Jupyter and Spider environment. Also I didn't understand why this isn't working on kaggle kernel.
Below is my code.
# Prepare X and y objects for sikitlearn
X = df.iloc[:, 1:5].values
y = df.iloc[:,-1].values
# Splitting the Dataset into the training set and the test set
X_train, X_test, y_train, y_test = train_test_split(X,y, test_size = 0.3, random_state =4)
Error Details:
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-49-5647b5a0596a> in <module>()
1 # Splitting the Dataset into the training set and the test set
2 from sklearn.model_selection import train_test_split
----> 3 X_train, X_test, y_train, y_test = train_test_split(X,y, test_size = 0.3, random_state =4)
/opt/conda/lib/python3.6/site-packages/sklearn/model_selection/_split.py in train_test_split(*arrays, **options)
2100
2101 return list(chain.from_iterable((safe_indexing(a, train),
-> 2102 safe_indexing(a, test)) for a in arrays))
2103
2104
/opt/conda/lib/python3.6/site-packages/sklearn/model_selection/_split.py in <genexpr>(.0)
2100
2101 return list(chain.from_iterable((safe_indexing(a, train),
-> 2102 safe_indexing(a, test)) for a in arrays))
2103
2104
/opt/conda/lib/python3.6/site-packages/sklearn/utils/__init__.py in safe_indexing(X, indices)
183 indices.dtype.kind == 'i'):
184 # This is often substantially faster than X[indices]
--> 185 return X.take(indices, axis=0)
186 else:
187 return X[indices]
TypeError: take_nd() got an unexpected keyword argument 'axis'