ValueError: Unknown label type: 'unknown'

I try to run following code. Btw, I am new to both python and sklearn.

import pandas as pd import numpy as np from sklearn.linear_model import LogisticRegression # data import and preparation trainData = pd.read_csv('train.csv') train = trainData.values testData = pd.read_csv('test.csv') test = testData.values X = np.c_[train[:, 0], train[:, 2], train[:, 6:7], train[:, 9]] X = np.nan_to_num(X) y = train[:, 1] Xtest = np.c_[test[:, 0:1], test[:, 5:6], test[:, 8]] Xtest = np.nan_to_num(Xtest) # model lr = LogisticRegression() lr.fit(X, y) 

where y is a np.ndarray of 0's and 1's

I receive the following:

File "C:\Anaconda3\lib\site-packages\sklearn\linear_model\logistic.py", line >1174, in fit check_classification_targets(y)

File "C:\Anaconda3\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: 'unknown'

from sklearn documentation:

y : array-like, shape (n_samples,) Target values (class labels in classification, real numbers in regression)

What is my error?

upd:

y is array([0.0, 1.0, 1.0, ..., 0.0, 1.0, 0.0], dtype=object) size is (891,)

2 Answers

Your y is of type object, so sklearn cannot recognize its type. Add the line y=y.astype('int') right after the line y = train[:, 1].

Adding to Miriam ,I also got the similar error but in my case individual elements of y_pred was of type 'np.int32' and individual elements of y was of type 'int'. I solved it by doing:

for i,x in enumerate(y_pred): y_pred[i]=x.astype('int')