TypeError: fit_transform() missing 1 required positional argument: 'X'
0
I am trying to do Feature Scaling in a dataset, but I get an error and have no idea how to proceed:
> Traceback (most recent call last):
>
> File "<ipython-input-10-71bea414b4d0>", line 22, in <module>
> x_train = sc_X.fit_transform(x_train)
>
> TypeError: fit_transform() missing 1 required positional argument: 'X'
and here is my code:
import pandas as pd
# Importing the dataset
dataset = pd.read_csv('Data.csv')
X = dataset.iloc[:, :-1].values
y = dataset.iloc[:, 3].values
# Taking care of missing data
from sklearn.preprocessing import Imputer
imputer = Imputer(missing_values="NaN", strategy="mean", axis=0)
imputer = Imputer.fit(imputer,X[:,1:3])
X[:, 1:3] = Imputer.transform(imputer,X[:, 1:3])
#Spliting the dataset into Training set and Test Set
from sklearn.cross_validation import train_test_split
x_train, x_test, y_train, y_test = train_test_split(X, y, test_size= 0.2, random_state= 0)
#Feature Scalling
from sklearn.preprocessing import StandardScaler
sc_X = StandardScaler
x_train = sc_X.fit_transform(x_train)
x_test = sc_X.transform(x_test)
python python-3.x
edited Jul 1 '18 at 17:54
Deduplicator
34.4k64888
asked Jul 1 '18 at 17:28
danyialKhandanyialKhan
724
add a comment |
0
I am trying to do Feature Scaling in a dataset, but I get an error and have no idea how to proceed:
> Traceback (most recent call last):
>
> File "<ipython-input-10-71bea414b4d0>", line 22, in <module>
> x_train = sc_X.fit_transform(x_train)
>
> TypeError: fit_transform() missing 1 required positional argument: 'X'
and here is my code:
import pandas as pd
# Importing the dataset
dataset = pd.read_csv('Data.csv')
X = dataset.iloc[:, :-1].values
y = dataset.iloc[:, 3].values
# Taking care of missing data
from sklearn.preprocessing import Imputer
imputer = Imputer(missing_values="NaN", strategy="mean", axis=0)
imputer = Imputer.fit(imputer,X[:,1:3])
X[:, 1:3] = Imputer.transform(imputer,X[:, 1:3])
#Spliting the dataset into Training set and Test Set
from sklearn.cross_validation import train_test_split
x_train, x_test, y_train, y_test = train_test_split(X, y, test_size= 0.2, random_state= 0)
#Feature Scalling
from sklearn.preprocessing import StandardScaler
sc_X = StandardScaler
x_train = sc_X.fit_transform(x_train)
x_test = sc_X.transform(x_test)
python python-3.x
edited Jul 1 '18 at 17:54
Deduplicator
34.4k64888
asked Jul 1 '18 at 17:28
danyialKhandanyialKhan
724
add a comment |
0
0
0
I am trying to do Feature Scaling in a dataset, but I get an error and have no idea how to proceed:
> Traceback (most recent call last):
>
> File "<ipython-input-10-71bea414b4d0>", line 22, in <module>
> x_train = sc_X.fit_transform(x_train)
>
> TypeError: fit_transform() missing 1 required positional argument: 'X'
and here is my code:
import pandas as pd
# Importing the dataset
dataset = pd.read_csv('Data.csv')
X = dataset.iloc[:, :-1].values
y = dataset.iloc[:, 3].values
# Taking care of missing data
from sklearn.preprocessing import Imputer
imputer = Imputer(missing_values="NaN", strategy="mean", axis=0)
imputer = Imputer.fit(imputer,X[:,1:3])
X[:, 1:3] = Imputer.transform(imputer,X[:, 1:3])
#Spliting the dataset into Training set and Test Set
from sklearn.cross_validation import train_test_split
x_train, x_test, y_train, y_test = train_test_split(X, y, test_size= 0.2, random_state= 0)
#Feature Scalling
from sklearn.preprocessing import StandardScaler
sc_X = StandardScaler
x_train = sc_X.fit_transform(x_train)
x_test = sc_X.transform(x_test)
python python-3.x
edited Jul 1 '18 at 17:54
Deduplicator
34.4k64888
asked Jul 1 '18 at 17:28
danyialKhandanyialKhan
724
I am trying to do Feature Scaling in a dataset, but I get an error and have no idea how to proceed:
> Traceback (most recent call last):
>
> File "<ipython-input-10-71bea414b4d0>", line 22, in <module>
> x_train = sc_X.fit_transform(x_train)
>
> TypeError: fit_transform() missing 1 required positional argument: 'X'
and here is my code:
import pandas as pd
# Importing the dataset
dataset = pd.read_csv('Data.csv')
X = dataset.iloc[:, :-1].values
y = dataset.iloc[:, 3].values
# Taking care of missing data
from sklearn.preprocessing import Imputer
imputer = Imputer(missing_values="NaN", strategy="mean", axis=0)
imputer = Imputer.fit(imputer,X[:,1:3])
X[:, 1:3] = Imputer.transform(imputer,X[:, 1:3])
#Spliting the dataset into Training set and Test Set
from sklearn.cross_validation import train_test_split
x_train, x_test, y_train, y_test = train_test_split(X, y, test_size= 0.2, random_state= 0)
#Feature Scalling
from sklearn.preprocessing import StandardScaler
sc_X = StandardScaler
x_train = sc_X.fit_transform(x_train)
x_test = sc_X.transform(x_test)
python python-3.x
python python-3.x
edited Jul 1 '18 at 17:54
Deduplicator
34.4k64888
asked Jul 1 '18 at 17:28
danyialKhandanyialKhan
724
edited Jul 1 '18 at 17:54
Deduplicator
34.4k64888
asked Jul 1 '18 at 17:28
danyialKhandanyialKhan
724
edited Jul 1 '18 at 17:54
Deduplicator
34.4k64888
edited Jul 1 '18 at 17:54
Deduplicator
34.4k64888
edited Jul 1 '18 at 17:54
Deduplicator
34.4k64888
34.4k64888
asked Jul 1 '18 at 17:28
danyialKhandanyialKhan
724
asked Jul 1 '18 at 17:28
danyialKhandanyialKhan
724
asked Jul 1 '18 at 17:28
danyialKhandanyialKhan
724
724
add a comment |
add a comment |
2 Answers
2
active
oldest
votes
2
sc_X = StandardScaler
should be:
sc_X = StandardScaler()
answered Jul 1 '18 at 17:57
Uku LoskitUku Loskit
30.4k86879
add a comment |
0
imputer is a method and Imputer is a class
So, change the code as below, and other such occurrences in this code:
imputer = imputer.fit(imputer,X[:,1:3])
edited Nov 22 '18 at 23:56
vahdet
1,57931130
answered Nov 22 '18 at 19:06
Aakif Mairaj MuftiAakif Mairaj Mufti
1
add a comment |
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2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
2
sc_X = StandardScaler
should be:
sc_X = StandardScaler()
answered Jul 1 '18 at 17:57
Uku LoskitUku Loskit
30.4k86879
add a comment |
2
sc_X = StandardScaler
should be:
sc_X = StandardScaler()
answered Jul 1 '18 at 17:57
Uku LoskitUku Loskit
30.4k86879
add a comment |
2
2
2
sc_X = StandardScaler
should be:
sc_X = StandardScaler()
answered Jul 1 '18 at 17:57
Uku LoskitUku Loskit
30.4k86879
sc_X = StandardScaler
should be:
sc_X = StandardScaler()
answered Jul 1 '18 at 17:57
Uku LoskitUku Loskit
30.4k86879
answered Jul 1 '18 at 17:57
Uku LoskitUku Loskit
30.4k86879
answered Jul 1 '18 at 17:57
Uku LoskitUku Loskit
30.4k86879
answered Jul 1 '18 at 17:57
Uku LoskitUku Loskit
30.4k86879
30.4k86879
add a comment |
add a comment |
0
imputer is a method and Imputer is a class
So, change the code as below, and other such occurrences in this code:
imputer = imputer.fit(imputer,X[:,1:3])
edited Nov 22 '18 at 23:56
vahdet
1,57931130
answered Nov 22 '18 at 19:06
Aakif Mairaj MuftiAakif Mairaj Mufti
1
add a comment |
0
imputer is a method and Imputer is a class
So, change the code as below, and other such occurrences in this code:
imputer = imputer.fit(imputer,X[:,1:3])
edited Nov 22 '18 at 23:56
vahdet
1,57931130
answered Nov 22 '18 at 19:06
Aakif Mairaj MuftiAakif Mairaj Mufti
1
add a comment |
0
0
0
imputer is a method and Imputer is a class
So, change the code as below, and other such occurrences in this code:
imputer = imputer.fit(imputer,X[:,1:3])
edited Nov 22 '18 at 23:56
vahdet
1,57931130
answered Nov 22 '18 at 19:06
Aakif Mairaj MuftiAakif Mairaj Mufti
1
imputer is a method and Imputer is a class
So, change the code as below, and other such occurrences in this code:
imputer = imputer.fit(imputer,X[:,1:3])
edited Nov 22 '18 at 23:56
vahdet
1,57931130
answered Nov 22 '18 at 19:06
Aakif Mairaj MuftiAakif Mairaj Mufti
1
edited Nov 22 '18 at 23:56
vahdet
1,57931130
edited Nov 22 '18 at 23:56
vahdet
1,57931130
edited Nov 22 '18 at 23:56
vahdet
1,57931130
1,57931130
answered Nov 22 '18 at 19:06
Aakif Mairaj MuftiAakif Mairaj Mufti
1
answered Nov 22 '18 at 19:06
Aakif Mairaj MuftiAakif Mairaj Mufti
1
answered Nov 22 '18 at 19:06
Aakif Mairaj MuftiAakif Mairaj Mufti
1
1
add a comment |
add a comment |
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