# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.## Licensed under the Apache License, Version 2.0 (the "License");# you may not use this file except in compliance with the License.# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0## Unless required by applicable law or agreed to in writing, software# distributed under the License is distributed on an "AS IS" BASIS,# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.# See the License for the specific language governing permissions and# limitations under the License.from AlgorithmImports import *from time import sleep### <summary>### Example algorithm showing how to use QCAlgorithm.train method### </summary>### <meta name="tag" content="using quantconnect" />### <meta name="tag" content="training" />class TrainingExampleAlgorithm(QCAlgorithm):'''Example algorithm showing how to use QCAlgorithm.train method'''def initialize(self):self.set_start_date(2013, 10, 7)self.set_end_date(2013, 10, 14)self.add_equity("SPY", Resolution.DAILY)# Set TrainingMethod to be executed immediatelyself.train(self.training_method)# Set TrainingMethod to be executed at 8:00 am every Sundayself.train(self.date_rules.every(DayOfWeek.SUNDAY), self.time_rules.at(8 , 0), self.training_method)def training_method(self):self.log(f'Start training at {self.time}')# Use the historical data to train the machine learning modelhistory = self.history(["SPY"], 200, Resolution.DAILY)# ML code:pass
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