CODEWITHSUNDEEP
pythonnumpyscikit-learn
J Ng
J Ng

Reputation: 799

Reshaping and Transpose issues

User1190882 has helped fix the tranpose issue. I will open a new thread for the SKlearn issue.

columns_train = np.array([df['A'], df['B'],  df['C'], df['D'], df['E'], df['F'], df['G']])
X = columns_train
Y = columns_target

X = np.transpose(X)
print np.shape(X)
print np.shape(Y)


X_train, X_test, Y_train, Y_test = train_test_split(X,Y,test_size = 0.2, random_state = 42)

clf = svm.LinearSVC()
clf.fit(X_train, Y_train)
print clf

File "C:\Python27\lib\site-packages\sklearn\utils\multiclass.py", line 172, in check_classification_targets
raise ValueError("Unknown label type: %r" % y_type)
ValueError: Unknown label type: 'continuous'

I am not sure what I can do to make this work after looking at other threads. Can you give me some advise please? Thanks

Upvotes: 2

Views: 231

Answers (1)

Prasad
Prasad

Reputation: 6034

Answer to before editing question

What you are looking for is 

X = np.transpose(X)

Answer after editing question

You get that continuous error when your datatype of your variable Y is of floating point type. In all classification type of problems, you have to maintain the label type as int. Convert the datatype of variable Y to int and then it should work fine.

Upvotes: 2

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