from openml.autorun import run_task
from sklearn import ensemble
import xmltodict
import os
"""
An example of an automated machine learning experiment using run_task
"""
key_file_path = "apikey.txt"
with open(key_file_path, 'r') as fh:
key = fh.readline()
task_id = 59
clf = ensemble.RandomForestClassifier()
connector = APIConnector(apikey=key)
task = connector.get_task(task_id)
prediction_path, description_path = run_task(task, clf)
prediction_abspath = os.path.abspath(prediction_path)
description_abspath = os.path.abspath(description_path)
return_code, response = connector.upload_run(prediction_abspath,
description_abspath)
if (return_code == 200):
response_dict = xmltodict.parse(response.content)
run_id = response_dict['oml:upload_run']['oml:run_id']
print("Uploaded run with id %s" % (run_id))
from openml.apiconnector import APIConnector
from openml.autorun import run_task
from sklearn import ensemble
import xmltodict
import os
"""
An example of an automated machine learning experiment using run_task
"""
key_file_path = "apikey.txt"
with open(key_file_path, 'r') as fh:
key = fh.readline()
task_id = 59
clf = ensemble.RandomForestClassifier()
connector = APIConnector(apikey = key)
task = connector.get_task(task_id)
prediction_path, description_path = run_task(task, clf)
prediction_abspath = os.path.abspath(prediction_path)
description_abspath = os.path.abspath(description_path)
return_code, response = connector.upload_run(prediction_abspath, description_abspath)
if(return_code == 200):
response_dict = xmltodict.parse(response.content)
run_id = response_dict['oml:upload_run']['oml:run_id']
print("Uploaded run with id %s" % (run_id))
