pyFTS.distributed package¶

Module contents¶

Submodules¶

pyFTS.distributed.dispy module¶

pyFTS.distributed.spark module¶

pyFTS.distributed.spark.create_multivariate_model(**parameters)[source]¶

pyFTS.distributed.spark.create_spark_conf(**kwargs)[source]¶

pyFTS.distributed.spark.create_univariate_model(**parameters)[source]¶

pyFTS.distributed.spark.distributed_predict(data, model, **kwargs)[source]¶

Parameters:	model – data – url – app –
Returns:

pyFTS.distributed.spark.distributed_train(model, data, **kwargs)[source]¶

Parameters:	model – data – url – app –
Returns:

pyFTS.distributed.spark.get_clustered_partitioner(explanatory_variables, target_variable, **parameters)[source]¶

pyFTS.distributed.spark.get_partitioner(shared_partitioner, type='common', variables=[])[source]¶

Parameters:	part –
Returns:

pyFTS.distributed.spark.get_variables(**parameters)[source]¶

pyFTS.distributed.spark.share_parameters(model, context, data)[source]¶

pyFTS.distributed.spark.slave_forecast_multivariate(data, **parameters)[source]¶

pyFTS.distributed.spark.slave_forecast_univariate(data, **parameters)[source]¶

Parameters:	data –
Returns:

pyFTS.distributed.spark.slave_train_multivariate(data, **parameters)[source]¶

pyFTS.distributed.spark.slave_train_univariate(data, **parameters)[source]¶

Parameters:	data –
Returns: