多种机器学习模型对不同特征数据集进行分类的结果汇总：对特征提取的全新思考（朱浩 杨家耀）

题目：多种机器学习模型对不同特征数据集进行分类的结果汇总：对特征提取的全新思考

主讲人：朱浩 杨家耀

时间：2020年12月27日上午10:30--11:30

地点：大理大学古城校区，工程学院 409

简介：1）多种机器学习模型对不同特征数据集进行分类的结果汇总：对特征提取的全新思考          

           2）时间序列数据集结果

参考资料：1.  Susto, Antonio G . Time-Series Classification Methods: Review and Applications to Power Systems Data[J]. Big Data Application in Power Systems, 2018:179-220.                                   

2.Deniz Ersan1 Chifumi Nishioka2 Ansgar Scherp3.Comparison of machine learning methods for fnancial time series forecasting at the examples of over 10 years of daily and hourly data of DAX 30 and S&P 500 Received: 17 June 2019 / Accepted: 24 October 2019  Springer Nature Singapore Pte Ltd. 2019

3.Hatami N , Gavet Y , Debayle J . Bag of recurrence patterns representation for time-series classification[J]. Pattern Analysis and Applications, 2019, 22(3):877-887.

4.Caporin M , Storti G . Financial Time Series: Methods and Models[J]. Journal of Risk and Financial Management, 2020, 13.

5.Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber, Deep learning for time series classification: a review[J]. DATA MINING AND KNOWLEDGE DISCOVERY, 2019