¿Cómo usar la lista de cadenas como datos de entrenamiento para svm usando scikit.learn?

I am using scikit.learn to train an svm based on data where each observation (X) is a list of words. The tags for each observation (Y) are floating point values. I have tried following the example given in the scikit learn documentation (http://scikit-learn.org/stable/modules/svm.html) for Multi-class classification. Here is my code:

from __future__ import division
from sklearn import svm
import os.path
import numpy

import re

'''
The stanford-postagger was included to see how it tags the words and to see if it would help in getting just the names
of the ingredients. Turns out its pointless.
'''
#from nltk.tag.stanford import POSTagger
mainDirectory = './nyu/PROJECTS/Epicurious/DATA/ingredients'
#st = POSTagger('/usr/share/stanford-postagger/models/english-bidirectional-distsim.tagger','/usr/share/stanford-postagger/stanford-postagger.jar')

'''
This is where we would reach each line of the file and then run a regex match on it to get all the words before
the first tab. (these are the names of the ingredients. Some of them may have adjectives like fresh, peeled,cut etc.
    Not sure what to do about them yet.)


'''
def getFileDetails(_filename,_fileDescriptor):
    rankingRegexMatch = re.match('([0-9](?:\_)[0-9]?)', _filename)

    if len(rankingRegexMatch.group(0)) == 2:
        ranking = float(rankingRegexMatch.group(0)[0])
    else:
        ranking = float(rankingRegexMatch.group(0)[0]+'.'+rankingRegexMatch.group(0)[2])

    _keywords = []
    for line in _fileDescriptor:
        m = re.match('(\w+\s*\w*)(?=\t[0-9])', line)
        if m:
            _keywords.append(m.group(0))

    return [_keywords,ranking]

'''
Open each file in the directory and pass the name and file descriptor to getFileDetails
'''
def this_is_it(files):
    _allKeywords = []
    _allRankings = []
    for eachFile in files:
        fullFilePath = mainDirectory + '/' + eachFile
        f = open(fullFilePath)
        XandYForThisFile = getFileDetails(eachFile,f)
        _allKeywords.append(XandYForThisFile[0])
        _allRankings.append(XandYForThisFile[1])
    #_allKeywords = numpy.array(_allKeywords,dtype=object)
    svm_learning(_allKeywords,_allRankings)



def svm_learning(x,y):
    clf = svm.SVC()
    clf.fit(x,y)
'''
This just prints the directory path and then calls the callback x on files
'''
def print_files( x, dir_path , files ):
    print dir_path
    x(files)
'''
code starts here
'''
os.path.walk(mainDirectory, print_files, this_is_it)

When the svm_learning(x,y) method is called, it throws me an error:

Traceback (most recent call last):
  File "scan for files.py", line 72, in <module>
    os.path.walk(mainDirectory, print_files, this_is_it)
  File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/posixpath.py", line 238, in walk
    func(arg, top, names)
  File "scan for files.py", line 68, in print_files
    x(files)
  File "scan for files.py", line 56, in this_is_it
    svm_learning(_allKeywords,_allRankings)
  File "scan for files.py", line 62, in svm_learning
    clf.fit(x,y)
  File "/Library/Python/2.7/site-packages/scikit_learn-0.14_git-py2.7-macosx-10.8-intel.egg/sklearn/svm/base.py", line 135, in fit
    X = atleast2d_or_csr(X, dtype=np.float64, order='C')
  File "/Library/Python/2.7/site-packages/scikit_learn-0.14_git-py2.7-macosx-10.8-intel.egg/sklearn/utils/validation.py", line 116, in atleast2d_or_csr
    "tocsr")
  File "/Library/Python/2.7/site-packages/scikit_learn-0.14_git-py2.7-macosx-10.8-intel.egg/sklearn/utils/validation.py", line 96, in _atleast2d_or_sparse
    X = array2d(X, dtype=dtype, order=order, copy=copy)
  File "/Library/Python/2.7/site-packages/scikit_learn-0.14_git-py2.7-macosx-10.8-intel.egg/sklearn/utils/validation.py", line 80, in array2d
    X_2d = np.asarray(np.atleast_2d(X), dtype=dtype, order=order)
  File "/Library/Python/2.7/site-packages/numpy-1.8.0.dev_bbcfcf6_20130307-py2.7-macosx-10.8-intel.egg/numpy/core/numeric.py", line 331, in asarray
    return array(a, dtype, copy=False, order=order)
ValueError: setting an array element with a sequence.

Can anyone help? I am new to scikit and could not find any help in the documentation.