I want to predict if user click on link or not. I use logistic regression. I have got a lot of data for start. But on 23 examples i didn't get this exception. If i try 3mio data the i get this exception
The following is my code, adapted from the example on the scikit-learn website:
data = [line.strip() for line in open('dataforSVM.txt')]
pod=[];
listData=[];
y=[];
for i in range(0,len(data)):
splitData=data[i].split(',' );
tempPod=[];
for j in range(0,len(splitData)-1):
if isFloat(splitData[j]):
tempPod.append(float(splitData[j]));
y.append(float(splitData[j]));
pod.append(tempPod)
X=pod;
Y=y;
h = .02 # step size in the mesh
logreg = linear_model.LogisticRegression(C=1.0, class_weight='auto', dual=False, fit_intercept=True,
intercept_scaling=1, penalty='l2', random_state=None, tol=0.0001)
Z=logreg.predict(X)
print Z
acc = accuracy_score(Y, Z)
print acc
I get error:
Traceback (most recent call last):
File "D:/Users/jures/Desktop/logisticRegression.py", line 45, in <module>
logreg.fit(X, Y)
File "C:\Python27\lib\site-packages\sklearn\svm\base.py", line 668, in fit
X = atleast2d_or_csr(X, dtype=np.float64, order="C")
File "C:\Python27\lib\site-packages\sklearn\utils\validation.py", line 134, in atleast2d_or_csr
"tocsr", force_all_finite)
File "C:\Python27\lib\site-packages\sklearn\utils\validation.py", line 111, in _atleast2d_or_sparse
force_all_finite=force_all_finite)
File "C:\Python27\lib\site-packages\sklearn\utils\validation.py", line 91, in array2d
X_2d = np.asarray(np.atleast_2d(X), dtype=dtype, order=order)
File "C:\Python27\lib\site-packages\numpy\core\numeric.py", line 320, in asarray
return array(a, dtype, copy=False, order=order)
ValueError: setting an array element with a sequence.
logreg.fit(X, Y)which I can't see in your code