def train(self, cloud=None, batch=False, api_key=None, version=None, **kwargs):
        """
        This is the basic training endpoint. Given an existing dataset this endpoint will train a model.

        Inputs
        api_key (optional) - String: Your API key, required only if the key has not been declared
          elsewhere. This allows the API to recognize a request as yours and automatically route it
          to the appropriate destination.
        cloud (optional) - String: Your private cloud domain, required only if the key has not been declared
          elsewhere. This allows the API to recognize a request as yours and automatically route it
          to the appropriate destination.
        """
        url_params = {"batch": batch, "api_key": api_key, "version": version, 'method': "train"}
        return self._api_handler(self.keywords['collection'], cloud=cloud, api="custom", url_params=url_params, **kwargs)
def train ( self , cloud = None , batch = False , api_key = None , version = None , ** kwargs ) : url_params = { "batch" : batch , "api_key" : api_key , "version" : version , 'method' : "train" } return self . _api_handler ( self . keywords [ 'collection' ] , cloud = cloud , api = "custom" , url_params = url_params , ** kwargs )
This is the basic training endpoint. Given an existing dataset this endpoint will train a model.

        Inputs
        api_key (optional) - String: Your API key, required only if the key has not been declared
          elsewhere. This allows the API to recognize a request as yours and automatically route it
          to the appropriate destination.
        cloud (optional) - String: Your private cloud domain, required only if the key has not been declared
          elsewhere. This allows the API to recognize a request as yours and automatically route it
          to the appropriate destination.