pyFTS/pyFTS/tests/hyperparam.py
2018-11-14 00:42:59 -02:00

28 lines
719 B
Python

import numpy as np
from pyFTS.hyperparam import GridSearch
def get_train_test():
from pyFTS.data import Malaysia
ds = Malaysia.get_data('temperature')[:2000]
# ds = pd.read_csv('Malaysia.csv',delimiter=',' )[['temperature']].values[:2000].flatten().tolist()
train = ds[:1000]
test = ds[1000:]
return 'Malaysia.temperature', train, test
hyperparams = {
'order':[1, 2, 3],
'partitions': np.arange(10,100,3),
'partitioner': [1,2],
'mf': [1, 2, 3, 4],
'lags': np.arange(1,35,2),
'alpha': np.arange(0,.5, .05)
}
nodes = ['192.168.0.110','192.168.0.106', '192.168.0.107']
ds, train, test = get_train_test()
GridSearch.execute(hyperparams, ds, train, test, nodes=nodes)