def __init__(self, datainfo, timeinfo):
'''
This constructor is supposed to initialize data members.
Use triple quotes for function documentation.
'''
# Just print some info from the datainfo variable
print(
"The Budget for this data set is: %d seconds" %
datainfo['time_budget'], 'name:', datainfo['name'])
print("Loaded %d time features, %d numerical features, %d categorical " \
"features and %d multi valued categorical variables" \
%(datainfo['loaded_feat_types'][0], datainfo['loaded_feat_types'][1],\
datainfo['loaded_feat_types'][2],datainfo['loaded_feat_types'][3]))
overall_spenttime = time.time() - timeinfo[0]
dataset_spenttime = time.time() - timeinfo[1]
print("[***] Overall time spent %5.2f sec" % overall_spenttime)
print("[***] Dataset time spent %5.2f sec" % dataset_spenttime)
self.num_train_samples = 0
self.num_feat = 1
self.num_labels = 1
self.is_trained = False
### install hyperopt and lightgbm ###
#print("AutoGBT[Model]:installing hyperopt and lightgbm...")
#setupmgr.pip_install("hyperopt")
#setupmgr.pip_install("lightgbm")
import StreamProcessor
self.mdl = StreamProcessor.StreamSaveRetrainPredictor()
self.score = []
self.batch_num = 0
def __init__(self,datainfo):
'''
This constructor is supposed to initialize data members.
Use triple quotes for function documentation.
'''
# Just print some info from the datainfo variable
self.num_train_samples=0
self.num_feat=1
self.num_labels=1
self.is_trained=False
### install hyperopt and lightgbm ###
print("AutoGBT[Model]:installing hyperopt and lightgbm...")
setupmgr.pip_install("hyperopt")
setupmgr.pip_install("lightgbm")
import StreamProcessor
self.mdl = StreamProcessor.StreamSaveRetrainPredictor()
