TypeError: 'module' object is not callable, cross_validation Python3

Question

TypeError: 'module' object is not callable

When trying to use cross_validation I get the error above. I'm not really sure how to solve this. Since I'm pretty new to this so I'd really appreciate any help.

import pandas as pd
import quandl, math
import numpy as np
from sklearn import preprocessing, svm, cross_validation
from sklearn.linear_model import LinearRegression

df = quandl.get('WIKI/GOOGL')
df = df [['Adj. Open','Adj. High','Adj. Low','Adj. Close','Adj. Volume',]]
df['HL_PCT'] = (df['Adj. High'] - df['Adj. Open']) / df['Adj. Open'] *  100
df['PCT_change'] = (df['Adj. Close'] - df['Adj. Open']) / df['Adj. Open'] *  100

df = df[['Adj. Close','HL_PCT','PCT_change','Adj. Volume']]

forecast_col = 'Adj. Close'
df.fillna(-99999, inplace=True)

forecast_out = int(math.ceil(0.01*len(df)))

df['label'] = df[forecast_col].shift(-forecast_out)
df.dropna(inplace=True)

x = np.array(df.drop(['label'],1))
y = np.array(df['label'])
x = preprocessing.scale(x)
y = np.array(df['label'])

x_train, x_test, y_train, y_test = cross_validation(x, y, test_size=0.2)

clf = LinearRegression
clf.fit(x_train, y_train)

accuracy = clf.score(x_test, y_test)

print(accuracy)

Answer 1

The name cross_validation identifies a module, the name of the function is train_test_split (see sklearn documentation ).

Use the dot notation to call the function instead:

cross_validation.train_test_split(x, y, test_size=0.2)