ValueError: Unknown label type: 'unknown'

PythonPandasNumpyScikit LearnLogistic Regression

Python Problem Overview


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: <http://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html#sklearn.linear_model.LogisticRegression.fit>

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,)

Python Solutions


Solution 1 - Python

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].

Solution 2 - Python

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')

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Content TypeOriginal AuthorOriginal Content on Stackoverflow
QuestionIvan ZhovannikView Question on Stackoverflow
Solution 1 - PythonMiriam FarberView Answer on Stackoverflow
Solution 2 - PythonAryan AgarwalView Answer on Stackoverflow