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Description
Description
DecisionTreeClassifier crashes with unknown label type: 'continuous-multioutput'. I've tried loading csv file using csv.reader, pandas.read_csv and some other stuff like parsing line-by-line.
Steps/Code to Reproduce
from sklearn import tree
feature_df = pd.read_csv(os.path.join(_PATH, 'features.txt'))
target_df = pd.read_csv(os.path.join(_PATH, 'target.txt'))
feature_df = feature_df._get_numeric_data()
target_df = target_df._get_numeric_data()
feature_df = feature_df.fillna(0)
target_df = target_df.fillna(0)
clf = tree.DecisionTreeClassifier()
clf_o = clf.fit(feature_df, target_df)
Expected Results
Error thrown informs user what REALLY is wrong, that f.e. his data set does not folllow assumptions (and what are those)
Actual Results
Traceback (most recent call last):
File "D:\Piotr\Documents\uni\bap\BAPFingerprintLocalisation\main.py", line 19,
in <module>
decision_tree.treeClassification()
File "D:\Piotr\Documents\uni\bap\BAPFingerprintLocalisation\code\decision_tree
.py", line 56, in treeClassification
clf_o = clf.fit(feature_df, target_df)
File "C:\Python35\lib\site-packages\sklearn\tree\tree.py", line 182, in fit
check_classification_targets(y)
File "C:\Python35\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-multioutput'
Versions
Windows-10-10.0.14393-SP0
Python 3.5.1 (v3.5.1:37a07cee5969, Dec 6 2015, 01:54:25) [MSC v.1900 64 bit (AMD64)]
NumPy 1.11.0
SciPy 0.17.1
Scikit-Learn 0.18
Update:
I've changed number of target variables to one, just to simplify things
clf_o = clf.fit(feature_df, target_df.ix[:,1])
Output: Unknown label type: 'continuous'
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