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def omega_fit(self, modelname, Xname, Yname=None, pure_python=True, **kwargs):
result = self.get_delegate(modelname).fit(*self.delegate_args, **self.delegate_kwargs)
return sanitized(result)
def omega_partial_fit(self,
modelname, Xname, Yname=None, pure_python=True, **kwargs):
result = self.get_delegate(modelname).partial_fit(*self.delegate_args, **self.delegate_kwargs)
return sanitized(result)
def omega_fit_transform(self, modelname, Xname, Yname=None, rName=None,
pure_python=True, **kwargs):
result = self.get_delegate(modelname).fit_transform(*self.delegate_args, **self.delegate_kwargs)
return sanitized(result)
def schedule_omegaml_job(self, nb_file, **kwargs):
"""
schedules the running of omegaml job
"""
result = self.om.jobs.schedule(nb_file)
return sanitized(result)
def omega_transform(self, modelname, Xname, rName=None, **kwargs):
result = self.get_delegate(modelname).transform(*self.delegate_args, **self.delegate_kwargs)
return sanitized(result)
def omega_score(self, modelname, Xname, Yname, rName=True, pure_python=True,
**kwargs):
result = self.get_delegate(modelname).score(*self.delegate_args, **self.delegate_kwargs)
return sanitized(result)
def omega_decision_function(self, modelname, Xname, rName=None, **kwargs):
result = self.get_delegate(modelname).decision_function(*self.delegate_args, **self.delegate_kwargs)
return sanitized(result)
def omega_predict(self, modelname, Xname, rName=None, pure_python=True, **kwargs):
result = self.get_delegate(modelname).predict(*self.delegate_args, **self.delegate_kwargs)
return sanitized(result)
def omega_gridsearch(self, modelname, Xname, Yname, parameters=None, **kwargs):
result = self.get_delegate(modelname).gridsearch(*self.delegate_args, **self.delegate_kwargs)
return sanitized(result)
def omega_predict_proba(self, modelname, Xname, rName=None, pure_python=True,
**kwargs):
result = self.get_delegate(modelname).predict_proba(*self.delegate_args, **self.delegate_kwargs)
return sanitized(result)