def local_predict(models, test_reader, output, method, prediction_info=None):
"""Get local predictions and combine them to get a final prediction
"""
local_model = MultiModel(models)
test_set_header = test_reader.has_headers()
for input_data in test_reader:
prediction = local_model.predict(input_data,
by_name=test_set_header,
method=method,
with_confidence=True)
u.write_prediction(prediction, output, prediction_info)
def local_predict(models, test_reader, output, method):
"""Get local predictions and combine them to get a final prediction
"""
local_model = MultiModel(models)
test_set_header = test_reader.has_headers()
for input_data in test_reader:
prediction = local_model.predict(input_data,
by_name=test_set_header,
method=method,
with_confidence=True)
u.write_prediction(prediction, output)
def local_predict(models, headers, test_reader, exclude, fields, method,
objective_field, output, test_set_header):
"""Get local predictions, combine them and save predictions to file
"""
local_model = MultiModel(models)
for row in test_reader:
for index in exclude:
del row[index]
input_data = fields.pair(row, headers, objective_field)
prediction = local_model.predict(input_data,
by_name=test_set_header,
method=method)
u.write_prediction(prediction, output)
def local_predict(models, test_reader, output, args, options=None,
exclude=None):
"""Get local predictions and combine them to get a final prediction
"""
local_model = MultiModel(models)
test_set_header = test_reader.has_headers()
for input_data in test_reader:
input_data_dict = test_reader.dict(input_data)
prediction = local_model.predict(
input_data_dict, by_name=test_set_header, method=args.method,
with_confidence=True, options=options,
missing_strategy=args.missing_strategy)
write_prediction(prediction, output,
args.prediction_info, input_data, exclude)
def local_predict(models,
test_reader,
output,
args,
options=None,
exclude=None):
"""Get local predictions and combine them to get a final prediction
"""
local_model = MultiModel(models)
test_set_header = test_reader.has_headers()
for input_data in test_reader:
input_data_dict = test_reader.dict(input_data)
prediction = local_model.predict(
input_data_dict,
by_name=test_set_header,
method=args.method,
with_confidence=True,
options=options,
missing_strategy=args.missing_strategy)
write_prediction(prediction, output, args.prediction_info, input_data,
exclude)
