pyFTS.hyperparam package

Module contents

Submodules

pyFTS.hyperparam.Util module

Common facilities for hyperparameter tunning

pyFTS.hyperparam.Util.create_hyperparam_tables(conn)

Create a sqlite3 table designed to store benchmark results.

Parameters:conn – a sqlite3 database connection

pyFTS.hyperparam.Util.insert_hyperparam(data, conn)

Insert benchmark data on database

Parameters:data – a tuple with the benchmark data with format:

Dataset: Identify on which dataset the dataset was performed Tag: a user defined word that indentify a benchmark set Model: FTS model Transformation: The name of data transformation, if one was used mf: membership function Order: the order of the FTS method Partitioner: UoD partitioning scheme Partitions: Number of partitions alpha: alpha cut lags: lags Measure: accuracy measure Value: the measure value

Parameters:conn – a sqlite3 database connection Returns:

pyFTS.hyperparam.Util.open_hyperparam_db(name)

Open a connection with a Sqlite database designed to store benchmark results.

Parameters:name – database filenem Returns:a sqlite3 database connection

pyFTS.hyperparam.GridSearch module

pyFTS.hyperparam.GridSearch.dict_individual(mf, partitioner, partitions, order, lags, alpha_cut)

pyFTS.hyperparam.GridSearch.execute(hyperparams, datasetname, train, test, **kwargs)

pyFTS.hyperparam.GridSearch.metodo_cluster(individual, train, test)