Community

Problem During application of linear regression

I am new to linear regression and machine learning.
I did the following... and ended up with a hugr error which ends with:
" ImportError: DLL load failed: The specified module could not be found. "
I don't understand how to solve this issue. I have all the modules installed. I'm using python 3.5.2, and the updated version of pip ( pip 9.0.1 )

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

quandl.ApiConfig.api_key = 'rb6SGMgaCHExRg6yos7N'
df = quandl.get('WIKI/GOOGL')

#print(df.head())

df = df[['Adj. Open', 'Adj. High', 'Adj. Low', 'Adj. Close', 'Adj. Volume']]
#print(df.head())
df['HL_PCT'] = ((df['Adj. High'] - df['Adj. Low']) / df['Adj. Low'] )*100.0

df['OC_PCT'] = ((df['Adj. Close'] - df['Adj. Open']) / df['Adj. Close'] )*100.0
###print(df.head())

##df = df[['OC_PCT', 'HL_PCT', 'Adj. Volume']]
###print(df.head())

forecast_col = 'Adj. Close'
##print(df[forecast_col])
df.fillna(value=-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)
X_train, X_test, y_train, y_test = cross_validation.train_test_split(X, y, test_size=0.2)
clf = svm.SVR()
clf.fit(X_train, y_train)
confidence = clf.score(X_test, y_test)
print(confidence)