摘要
机器人与机器学习每日新闻的新闻记者兼工作人员新闻编辑-人工智能的新数据出现在一份新的报告中。根据NewsRx记者在摩洛哥Kenitra的新闻报道，研究表明，“高频交易利用强大的数学算法以极快的速度执行交易，这使得使用机器学习技术进行预测是必要的。本文评估了各种集成学习算法的有效性，包括Boos Ting(Adaboost和XGBoost)、Bagging(Random Forest and Bagging-LSVM)和St使用卡萨布兰卡证券交易所的(HFT)数据预测股票价格。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Fresh data on artificial intelligence are present ed in a new report. According to news reporting from Kenitra, Morocco, by NewsRx journalists, research stated, “High-Frequency Trading utilizes powerful mathema tical algorithms to execute transactions at an extremely rapid pace, which makes the use of machine learning techniques for prediction necessary. This paper eva luates the effectiveness of various ensemble learning algorithms, including Boos ting (Adaboost and XGBoost), Bagging (Random Forest and Bagging-LSVM), and Stack ing, in predicting stock prices using High-Frequency Trading (HFT) data from the Casablanca Stock Exchange.”
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