Showing Error while using train_test_Split method to on Kaggle kernal. Help appreciated
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'
python python-3.x scikit-learn kernel
add a comment |
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'
python python-3.x scikit-learn kernel
Looks like you have encountered this issue. Try updating your scikit-learn, numpy and pandas. Show the dtypes for thedf
. Are any of the columns of categorical type in pandas DataFrame?
– Vivek Kumar
Nov 15 '18 at 7:23
I find the solution , I just removed ".values" from my code and it works for me.
– Ravi Varma
Nov 17 '18 at 4:18
add a comment |
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'
python python-3.x scikit-learn kernel
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'
python python-3.x scikit-learn kernel
python python-3.x scikit-learn kernel
edited Nov 15 '18 at 4:55
Ravi Varma
asked Nov 15 '18 at 4:30
Ravi VarmaRavi Varma
34
34
Looks like you have encountered this issue. Try updating your scikit-learn, numpy and pandas. Show the dtypes for thedf
. Are any of the columns of categorical type in pandas DataFrame?
– Vivek Kumar
Nov 15 '18 at 7:23
I find the solution , I just removed ".values" from my code and it works for me.
– Ravi Varma
Nov 17 '18 at 4:18
add a comment |
Looks like you have encountered this issue. Try updating your scikit-learn, numpy and pandas. Show the dtypes for thedf
. Are any of the columns of categorical type in pandas DataFrame?
– Vivek Kumar
Nov 15 '18 at 7:23
I find the solution , I just removed ".values" from my code and it works for me.
– Ravi Varma
Nov 17 '18 at 4:18
Looks like you have encountered this issue. Try updating your scikit-learn, numpy and pandas. Show the dtypes for the
df
. Are any of the columns of categorical type in pandas DataFrame?– Vivek Kumar
Nov 15 '18 at 7:23
Looks like you have encountered this issue. Try updating your scikit-learn, numpy and pandas. Show the dtypes for the
df
. Are any of the columns of categorical type in pandas DataFrame?– Vivek Kumar
Nov 15 '18 at 7:23
I find the solution , I just removed ".values" from my code and it works for me.
– Ravi Varma
Nov 17 '18 at 4:18
I find the solution , I just removed ".values" from my code and it works for me.
– Ravi Varma
Nov 17 '18 at 4:18
add a comment |
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Looks like you have encountered this issue. Try updating your scikit-learn, numpy and pandas. Show the dtypes for the
df
. Are any of the columns of categorical type in pandas DataFrame?– Vivek Kumar
Nov 15 '18 at 7:23
I find the solution , I just removed ".values" from my code and it works for me.
– Ravi Varma
Nov 17 '18 at 4:18