I'm trying to add a custom regressor to a pipeline.
For debugging purposes I commented everything out.
class myRegressor(BaseEstimator, TransformerMixin):
def __init__(self, k=0, njobs=1, cv=6, nestimators=50):
pass
def fit(self, X, y=None):
return self
def transform(self, X):
return X
# main here with some code
estimators = [('my_regressor'), myRegressor(k=args.k, cv=args.cv),
('scaler', preprocessing.StandardScaler()),
('rbf', svm.SVC(class_weight='auto',
kernel='rbf',
random_state=i))]
try:
clf_pipeline = Pipeline(estimators)
parameters = dict(rbf__C=c_range,
rbf__gamma=gamma_range)
clf = grid_search.GridSearchCV(clf_pipeline,
param_grid=parameters,
cv=args.cv,
n_jobs=args.njobs)
clf.fit(x_train, y_train)
except Exception, e:
print "Could not complete grid search (rbf SVM)"
print str(e)
sys.exit(1)
With the code below, I'm getting:
Could not complete grid search (rbf SVM)
dictionary update sequence element #0 has length 18; 2 is required
The problem seems to be myRegressor, because gridsearch does complete without
it in the pipeline.
I've done this before and I'm not sure what I'm doing wrong here.
Thank you,
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