x = iv_train
y = dv_train
dy = dv_train.shape[0]

def huber_loss(m, b, x, y, dy, c=2):
                y_fit = m * x + b
                t = abs((y - y_fit) / dy)
                flag = t > c
                return np.sum((~flag) * (0.5 * t ** 2) - (flag) * c * (0.5 * c - t), -1)

def ls_loss(m, b, x, y):
              y_fit = m * x + b
              return np.sum(((y - y_fit)) ** 2, -1)

from xml.dom import minidom
xmldoc = minidom.parse('config.xml')

lossfn = xmldoc.getElementsByTagName('lossfn')[0].childNodes[0].nodeValue.strip()

if (lossfn == 'huber'):
    lossfn = huber_loss
else :
    lossfn = ls_loss

params = {'n_estimators': n_estimators, 'max_depth': max_depth, 'min_samples_split': min_samples_split, 'subsample' : subsample,
          'learning_rate': learning_rate , 'loss': lossfn ,'min_samples_leaf': 1, 'max_features' : max_features}

model = ensemble.GradientBoostingRegressor(**params)
model.fit(iv_train, dv_train)

This is the error I'm getting while running model.fit

....model.fit(iv_train, dv_train)
C:UsersdellAnaconda3libsite-packagessklearnutilsvalidation.py:761: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
  y = column_or_1d(y, warn=True)
Traceback (most recent call last):

  File "<ipython-input-9-addb50fde228>", line 1, in <module>
    model.fit(iv_train, dv_train)

  File "C:UsersdellAnaconda3libsite-packagessklearnensemblegradient_boosting.py", line 1414, in fit
    self._check_params()

  File "C:UsersdellAnaconda3libsite-packagessklearnensemblegradient_boosting.py", line 1218, in _check_params
    raise ValueError("Loss '{0:s}' not supported. ".format(self.loss))

TypeError: unsupported format string passed to function.__format__