ValueError: unknown wird in sklearn.RFECV nicht unterstützt

Ich habe versucht, die Anzahl der Funktionen, die für meinen Klassifikator wirklich relevant sind, mit rfecv einzugrenzen. Dies ist der Code, den ich geschrieben habe

import sklearn
import pandas as p
import numpy as np
import scipy as sp
import pylab as pl
from sklearn import linear_model, cross_validation, metrics
from sklearn.svm import SVC
from sklearn.feature_selection import RFECV
from sklearn.metrics import zero_one_loss
from sklearn import preprocessing
#from sklearn.feature_extraction.text import CountVectorizer
#from sklearn.feature_selection import SelectKBest, chi2

modelType = "notext"

# ----------------------------------------------------------
# Prepare the Data
# ----------------------------------------------------------
training_data = np.array(p.read_table('F:/NYC/NYU/SM/3/SNLP/Project/Data/train.tsv'))
print ("Read Data\n")

# get the target variable and set it as Y so we can predict it
Y = training_data[:,-1]

print(Y)

# not all data is numerical, so we'll have to convert those fields
# fix "is_news":
training_data[:,17] = [0 if x == "?" else 1 for x in training_data[:,17]]

# fix -1 entries in hasDomainLink
training_data[:,14] = [0 if x =="-1" else x for x in training_data[:,10]]

# fix "news_front_page":
training_data[:,20] = [999 if x == "?" else x for x in training_data[:,20]]
training_data[:,20] = [1 if x == "1" else x for x in training_data[:,20]]
training_data[:,20] = [0 if x == "0" else x for x in training_data[:,20]]

# fix "alchemy category":
training_data[:,3] = [0 if x=="arts_entertainment" else x for x in training_data[:,3]]
training_data[:,3] = [1 if x=="business" else x for x in training_data[:,3]]
training_data[:,3] = [2 if x=="computer_internet" else x for x in training_data[:,3]]
training_data[:,3] = [3 if x=="culture_politics" else x for x in training_data[:,3]]
training_data[:,3] = [4 if x=="gaming" else x for x in training_data[:,3]]
training_data[:,3] = [5 if x=="health" else x for x in training_data[:,3]]
training_data[:,3] = [6 if x=="law_crime" else x for x in training_data[:,3]]
training_data[:,3] = [7 if x=="recreation" else x for x in training_data[:,3]]
training_data[:,3] = [8 if x=="religion" else x for x in training_data[:,3]]
training_data[:,3] = [9 if x=="science_technology" else x for x in training_data[:,3]]
training_data[:,3] = [10 if x=="sports" else x for x in training_data[:,3]]
training_data[:,3] = [11 if x=="unknown" else x for x in training_data[:,3]]
training_data[:,3] = [12 if x=="weather" else x for x in training_data[:,3]]
training_data[:,3] = [999 if x=="?" else x for x in training_data[:,3]]

print ("Corrected outliers data\n")

# ----------------------------------------------------------
# Models
# ----------------------------------------------------------
if modelType == "notext":
    print ("no text model\n")
    #ignore features which are useless
    X = training_data[:,list([3, 5, 6, 7, 8, 9, 10, 14, 15, 16, 17, 19, 20, 22, 25])]
    scaler = preprocessing.StandardScaler()
    print("initialized scaler \n")
    scaler.fit(X,Y)
    print("fitted train data and labels\n")
    X = scaler.transform(X)
    print("Transformed train data\n")
    svc = SVC(kernel = "linear")
    print("Initialized SVM\n")
    rfecv = RFECV(estimator = svc, cv = 5, loss_func = zero_one_loss, verbose = 1)
    print("Initialized RFECV\n")
    rfecv.fit(X,Y)
    print("Fitted train data and label\n")
    rfecv.support_
    print ("Optimal Number of features : %d" % rfecv.n_features_)
    savetxt('rfecv.csv', rfecv.ranking_, delimiter=',', fmt='%f')

Beim Aufruf von "rfecv.fit (X, Y)" löst mein Code einen Fehler aus der Datei metrices.py aus. "ValueError: unknown wird nicht unterstützt."

Der Fehler sprießt insklearn.metrics.metrics:

# No metrics support "multiclass-multioutput" format
    if (y_type not in ["binary", "multiclass", "multilabel-indicator", "multilabel-sequences"]):
        raise ValueError("{0} is not supported".format(y_type))

Dies ist ein Klassifizierungsproblem, Zielwerte nur 0 oder 1. Der Datensatz befindet sich unterKaggle-Wettbewerbsdaten

Wenn jemand darauf hinweisen kann, wo ich falsch liege, würde ich es begrüßen.